JP7666376B2 - Diagnostic device, diagnostic method, and diagnostic program - Google Patents

Description

The present invention relates to a diagnostic device, a diagnostic method, and a diagnostic program.

A Coriolis mass flowmeter is known as one type of flowmeter used in plants. A Coriolis mass flowmeter vibrates a vibrating tube (U-shaped tube) through which a fluid flows by exciting a coil, and measures the Coriolis force generated by the fluid passing inside the vibrating tube via the twisting of the vibrating tube. Because the Coriolis force increases in accordance with the fluid flow rate, it is possible to measure the flow rate via the width and phase of the twisting of the vibrating tube.

Coriolis mass flowmeters use the twisting of the vibrating tube to measure the flow rate, so if the vibrating tube becomes corroded, errors will occur in the flow rate measurement. It is also desirable to be aware of corrosion for the sake of maintaining the vibrating tube.

Patent No. 4952820 Patent No. 4469337 Patent No. 4866423 Patent No. 3523592 Patent No. 7024466

However, the above-mentioned conventional technologies leave room for improvement in terms of accurately diagnosing the condition of the vibrating tube of a Coriolis mass flowmeter. For example, in Patent Document 1, amplitude information is used to determine corrosion of the vibrating tube, which is affected by the amplification sensitivity of the drive circuit and measurement circuit. In addition, in Patent Document 1, corrosion of the vibrating tube is determined based on rigidity, and the change in wall thickness is not directly determined.

The present invention has been made in consideration of the above, and aims to accurately diagnose the condition of the vibrating tube of a Coriolis mass flowmeter.

The present invention provides a diagnostic device that includes a transceiver unit that acquires a density calibration result related to the calibration of the density of a fluid generated by calibrating a Coriolis mass flowmeter that measures the flow rate and density of a fluid flowing through a vibrating tube based on the Coriolis force acting on the vibrating tube, and a thickness and stiffness diagnostic unit that performs a calculation related to at least one of the thickness and stiffness of the vibrating tube based on the density calibration result and generates a thickness and stiffness diagnostic result related to a change in the vibrating tube.

The present invention also provides a diagnostic method in which a computer acquires density calibration results relating to the calibration of the density of a fluid generated by calibrating a Coriolis mass flowmeter that measures the flow rate and density of a fluid flowing through a vibrating tube based on the Coriolis force acting on the vibrating tube, performs calculations relating to at least one of the thickness and stiffness of the vibrating tube based on the density diagnostic results, and generates thickness stiffness diagnostic results relating to changes in the vibrating tube.

The present invention also provides a diagnostic program that causes a computer to execute a process that acquires density calibration results related to the calibration of the density of a fluid generated by calibrating a Coriolis mass flowmeter that measures the flow rate and density of a fluid flowing through a vibrating tube based on the Coriolis force acting on the vibrating tube, performs a calculation related to at least one of the thickness and stiffness of the vibrating tube based on the density diagnostic result, and generates a thickness stiffness diagnostic result related to a change in the vibrating tube.

The present invention has the effect of enabling accurate diagnosis of the condition of the vibrating tube of a Coriolis mass flowmeter.

FIG. 1 is a diagram illustrating an example of the configuration of a diagnostic system according to an embodiment. 1 is a block diagram showing an example of the configuration of a Coriolis mass flowmeter according to an embodiment; FIG. 4 is a diagram illustrating an example of a measurement process of the Coriolis mass flowmeter according to the embodiment. FIG. 2 is a block diagram showing an example of the configuration of each device of the diagnostic system according to the embodiment. FIG. 11 is a diagram showing an example of an entire density calibration process according to the embodiment. FIG. 11 is a diagram illustrating an example of a density calibration process according to the embodiment. FIG. 11 is a diagram illustrating an example of an overall density error diagnosis process according to the embodiment. FIG. 2 is a diagram illustrating an example of a density error diagnosis process 1 according to the embodiment. FIG. 11 is a diagram illustrating an example of a density error diagnosis process 2 according to the embodiment. FIG. 11 is a diagram illustrating an example of a density error diagnosis process 3 according to the embodiment. FIG. 11 is a diagram showing an example of an entire thickness stiffness diagnosis process according to the embodiment; 1 is a diagram showing an example of a wall thickness rigidity diagnosis process 1 according to an embodiment; FIG. 11 is a diagram showing an example of a wall thickness rigidity diagnosis process 2 according to the embodiment. FIG. 11 is a diagram showing an example of a wall thickness rigidity diagnosis process 3 according to the embodiment. FIG. 11 is a diagram showing an example of a thickness rigidity diagnosis process 4 according to the embodiment. FIG. 11 is a diagram showing an example of a wall thickness rigidity diagnosis process 5 according to the embodiment. 6 is a diagram showing an example of the entire flow rate error diagnosis and simple correction process according to the embodiment; FIG. 5A to 5C are diagrams illustrating an example of a flow rate error diagnosis and simple correction process 1 according to the embodiment. 11A and 11B are diagrams illustrating an example of a flow rate error diagnosis and simple correction process 2 according to the embodiment. 11A and 11B are diagrams illustrating an example of a flow rate error diagnosis and simple correction process 3 according to the embodiment. FIG. 11 is a diagram showing an example of a flow rate error diagnosis and simple correction process 4 according to the embodiment. FIG. 4 is a diagram showing an example of an entire timing prediction diagnosis process according to the embodiment; FIG. 2 is a diagram illustrating an example of a timing prediction diagnosis process 1 according to the embodiment. FIG. 4 is a diagram illustrating an example of a timing prediction diagnosis process 2 according to the embodiment. FIG. 11 is a diagram illustrating an example of a timing prediction diagnosis process 3 according to the embodiment. FIG. 11 is a diagram illustrating an example of a timing prediction diagnosis process 4 according to the embodiment. FIG. 11 is a diagram showing an example of a density diagnosis result according to the embodiment. FIG. 11 is a diagram showing an example of a wall thickness rigidity diagnosis result 1 according to the embodiment. FIG. 11 is a diagram for explaining a wall thickness rigidity diagnosis result 2 according to the embodiment. FIG. 11 is a diagram showing an example of a wall thickness rigidity diagnosis result 2 according to the embodiment. FIG. 3 is a diagram showing an example of a thickness rigidity diagnosis result 3-1 according to the embodiment. FIG. 3 is a diagram showing an example of a thickness rigidity diagnosis result 3-2 according to the embodiment. FIG. 4 is a diagram showing an example of a flow rate diagnosis result 1 according to the embodiment. FIG. 2 is a diagram showing an example of a flow rate diagnosis result 2-1 according to the embodiment. FIG. 2 is a diagram showing an example of a flow rate diagnosis result 2-2 according to the embodiment. FIG. 11 is a diagram showing an example of a flow rate diagnosis result 2-3 according to the embodiment. FIG. 11 is a diagram showing an example of a timing prediction diagnosis result according to the embodiment. 10 is a flowchart showing an example of the overall flow of diagnostic processing according to the embodiment. 1 is a flowchart showing an example of an overall flow of a density calibration process according to an embodiment. 10 is a flowchart showing an example of the overall flow of a density error diagnosis process according to the embodiment. 10 is a flowchart showing an example of the overall flow of a thickness stiffness diagnosis process according to the embodiment. 10 is a flowchart showing an example of the overall flow rate diagnosis and simple correction process according to the embodiment. 5 is a flowchart showing an example of the overall flow of a timing prediction diagnosis process according to the embodiment. FIG. 2 is a diagram illustrating an example of a hardware configuration according to an embodiment.

Below, a diagnostic device, diagnostic method, and diagnostic program according to one embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiment described below.

[Embodiment]
The configuration of the diagnostic system (1000) according to this embodiment, the configuration of the Coriolis mass flowmeter (1), the configuration of each device in the diagnostic system (1000), details of each process of the calibration device (3) and the diagnostic device (2), the results of each process, and the flow of each process will be described below in order, and finally the effects of this embodiment will be described.

1. Configuration of diagnostic system (1000)
The configuration of the diagnostic system (1000) according to this embodiment will be described in detail with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of the diagnostic system (1000) according to the embodiment. Below, an example of the overall configuration of the diagnostic system (1000), the processing of the diagnostic system (1000), the basic operation of the Coriolis mass flowmeter (1), and problems with the conventional technology will be described in this order, and finally, the effects of the diagnostic system (1000) will be described.

(1-1. Example of the overall configuration of the diagnostic system (1000))
The diagnostic system (1000) includes a Coriolis mass flowmeter (1), a diagnostic device (2), and a calibration device (3). Here, the Coriolis mass flowmeter (1), the diagnostic device (2), and the calibration device (3) are connected to each other so as to be able to communicate with each other by wire or wirelessly via a predetermined communication network (not shown). The diagnostic system (1000) shown in FIG. 1 may include a plurality of Coriolis mass flowmeters (1), a plurality of diagnostic devices (2), and a plurality of calibration devices (3). As will be described later in FIG. 2, the Coriolis mass flowmeter (1) may have at least one of the diagnostic device (2) and the calibration device (3) as an internal device. Furthermore, the diagnostic device (2) and the calibration device (3) may be integrated as an external device (31).

(1-2. Overall processing of the diagnostic system (1000))
The overall processing of the diagnostic system (1000) as described above will be described. First, the calibration device (3) acquires the measured value measured by the Coriolis mass flowmeter (1) (step S1). Next, the calibration device (3) executes density calibration processing (step S2) of the Coriolis mass flowmeter (1). Next, the diagnostic device (2) acquires the density calibration result (151) from the calibration device (3) (step S3), and executes density error diagnosis processing (step S4), wall thickness rigidity diagnosis processing (step S5), flow rate error diagnosis and simple correction processing (step S6), and timing prediction diagnosis processing (step S7) in this order. Then, the diagnostic device (2) transmits the diagnosis results of the above steps S4 to S7 to the Coriolis mass flowmeter (1) (step S8). In addition, the diagnostic device (2) transmits the calibration timing of the Coriolis mass flowmeter (1), which is the timing prediction diagnosis result of the above step S7, to the calibration device (3) (step S9). Note that the above steps S1 to S9 can be executed in a different order. Furthermore, among the above steps S1 to S9, some of the processes may be omitted.

(1-3. Basic operation of Coriolis mass flowmeter (1))
2 to 3 and equations, a basic operation of the Coriolis mass flowmeter (1) in the diagnostic system (1000) will be described. The basic configuration, measurement equation, and operation of the Coriolis mass flowmeter (1) will be described in that order below.

(1-3-1. Basic configuration of Coriolis mass flowmeter (1))
The basic configuration of the Coriolis mass flowmeter (1) will be described with reference to Fig. 2. Fig. 2 is a block diagram showing an example of the configuration of the Coriolis mass flowmeter (1) according to the embodiment. As shown in Fig. 2, the Coriolis mass flowmeter (1) has a detection unit (10), a conversion unit (20), and a display operation unit (30). In addition, the Coriolis mass flowmeter (1) is connected to an external device (31).

The detection unit (10) has one or more vibration tubes (11), a vibration unit (12), two or more sensors (13, 14) that measure vibration, and a temperature sensor (15). Here, the upstream sensor (13) transmits an upstream signal S1 (13a) to the conversion unit (20). Also, the downstream sensor (14) transmits a downstream signal S2 (14a) to the conversion unit (20). The temperature sensor (15) measures at least one of the temperature of the vibration tube (11) and the temperature of the fluid, and transmits a temperature signal T (15a) to the conversion unit (20). The vibration unit (12) receives an excitation signal drive (12a) from the conversion unit (20) and vibrates the vibration tube (11).

The conversion unit (20) has a drive control unit (21), a mass flow rate calculation unit (22), and a density calculation unit (23). The drive control unit (21) changes the excitation signal drive (12a) so that at least one of the amplitudes of the upstream signal S1 (13a) and the downstream signal S2 (14a) becomes a target value. The mass flow rate calculation unit (22) calculates the mass flow rate from the phase difference and frequency of the upstream signal S1 (13a) and the downstream signal S2 (14a). The mass flow rate calculation unit (22) also performs temperature correction using the temperature signal T (15a). The density calculation unit (23) calculates the density of the fluid from at least one of the frequency of the upstream signal S1 (13a) and the frequency of the downstream signal S2 (14a). The density calculation unit (23) also performs temperature correction using the temperature signal T (15a).

The conversion unit (20) transmits the measured numerical value to the display operation unit (30) as a status value (32a). The conversion unit (20) also transmits the measured numerical value to the external device (31) as a status value (32b). Meanwhile, the display operation unit (30) transmits an operation amount (33a) to the conversion unit (20) and sets the operation and the measurement coefficient. The external device (31) also transmits an operation amount (33b) to the conversion unit (20) and sets the operation and the measurement coefficient.

The conversion unit (20) may also have a calibration control unit (40b) that performs a calibration process for measuring at least one of the mass flow rate and the density of the Coriolis mass flowmeter (1). The conversion unit (20) may also have a diagnosis control unit (60b) that performs a diagnosis process for the Coriolis mass flowmeter (1).

The external device (31) holds a reference flow meter and calibrates the Coriolis mass flow meter (1) by flowing a fluid, and has a calibration control unit (40a) and a diagnosis control unit (60a). The calibration control unit (40a) has a density calibration unit (51a) and a mass flow calibration unit (41a). The density calibration unit (51a) performs a density calibration process by measuring the frequency of multiple fluids with known densities. The mass flow calibration unit (41a) performs a mass flow calibration process. In addition, the diagnosis control unit (60a) performs a diagnosis process by a diagnosis device (2) according to an embodiment described later.

On the other hand, the calibration control unit (40b) of the conversion unit (20) of the Coriolis mass flowmeter (1) can also execute a calibration process, similar to the calibration control unit (40a) of the external device (31) described above. Also, the diagnosis control unit (60b) of the conversion unit (20) of the Coriolis mass flowmeter (1) can execute a diagnosis process by a diagnosis device (2) according to an embodiment described later, similar to the diagnosis control unit (60a) of the external device (31) described above.

As described above, in the diagnostic system (1000) according to the embodiment, the diagnostic control unit (60) that executes various diagnostic processes is configured as either or both of the diagnostic control unit (60a) possessed by the external device (31) and the diagnostic control unit (60b) possessed by the conversion unit (20) inside the Coriolis mass flowmeter (1).

(1-3-2. Measurement equation of Coriolis mass flowmeter (1))
The measurement formula of the Coriolis mass flowmeter (1) will be described below. First, according to JIS B7555 "Explanation of flow measurement method by Coriolis meter (mass flow rate, density and volumetric flow rate measurement)", the mass flow rate Qm is measured by the following formula (1).

Here, the variable Ks indicates the rigidity (spring constant) of the vibrating tube in the torsional direction. The variable ω indicates the vibration angular velocity of the vibrating tube. The variable d indicates the width of the U-shaped vibrating tube. The variable L indicates the length of the U-shaped vibrating tube in the vibration direction. The variable K1 indicates a constant. The variable ωs indicates the natural frequency in the torsional direction. The variable ωu indicates the natural angular frequency in the vibration direction. The variable θ0 indicates the phase difference corresponding to the twist.

To measure the actual mass flow rate, the following measurement formula (2) is used.

In the Coriolis mass flowmeter (1), the vibrating tube vibration frequency f and the phase difference θ0 are measured and multiplied by the flow measurement coefficient Cq to obtain the mass flow rate Qm. At this time, the flow measurement coefficient Cq is calculated by the mass flow calibration unit (41) and is defined as the flow measurement coefficient Cq (28f). The phase difference θ0 is also measured and is defined as the phase difference θ (28d). The frequency f is also measured and is defined as the frequency f (28c). The mass flow rate Qm is then calculated using the above formula (2) and is defined as the mass flow rate Qm (28a).

In the vibration of the vibrating tube (11) of the Coriolis mass flowmeter (1), the relationship between the stiffness (spring constant) K of the vibrating tube (11), the total mass M of the vibrating tube (11), and the vibration angular frequency ω of the vibrating tube (11) is expressed by the following equation (3). Here, the variable f indicates the vibration frequency of the vibrating tube (11).

The total mass M of the vibration tube (11) is the sum of the mass Mu of the vibration tube (11), the mass Md of the accessories connected to the vibration tube (11), such as two or more sensors (13, 14) and the vibration unit (12), and the mass Mf of the fluid in the vibration tube (11), and is expressed by the following (4).

The mass Mf of the fluid in the vibrating tube (11) is expressed by the following equation (5) using the volume of the fluid, i.e., the internal volume V of the vibrating tube (11), and the density ρ of the fluid.

Here, from the above equations (3), (4), and (5), the following equations (6) and (7) are given.

Here, density ρ is a function of vibration frequency f. The above formula (7) includes the rigidity K of the vibrating tube (11), the internal volume V of the vibrating tube (11), the mass Mu of the vibrating tube (11) itself, and the mass Md of the accessories. Therefore, these coefficients must be calculated in order to measure density.

Measure a fluid with a known density ρ. If the density is ρa, the vibration frequency is fa, and the rigidity of the vibrating tube (11) is Ka, the following equation (8) holds from the above equation (6).

If the stiffness Ka of the vibrating tube (11) is equal to the stiffness K of the vibrating tube (11) at the time of measurement, it is expressed by the following formula (9).

Note that the rigidity of the vibration tube (11) changes depending on temperature, etc., so strictly speaking, the above formula (9) does not hold. Therefore, correction based on temperature, etc. is required.

From the above equations (6), (8), and (9), the following equation (10) holds.

Here, we define the density measurement coefficient Cd. As expressed in the following formula (11), the density measurement coefficient Cd is the sum of the mass of the vibration tube and accessories divided by the internal volume of the vibration tube, and has the same units as density.

Furthermore, from the above equations (10) and (11), the following equations (12) and (13) hold true.

In the Coriolis mass flowmeter (1), the density measurement coefficient Cd and frequency fa are determined by the density calibration unit (51) and are defined as the density measurement coefficient Cd (28k) and the density measurement coefficient fa (28l), respectively. In addition, the vibration frequency f of the vibration tube (11) is measured and defined as frequency f (28c). Then, the density ρ is calculated from the above formula (12) and defined as density ρ (28b).

Here, the above formula (12) shows that if the density measurement coefficient Cd and the frequency fa at fluid density ρa are measured in advance, the density ρ of an unknown fluid can be calculated from the frequency f. In this case, the fluid density ρa and frequency fa use the values of air or vacuum at standard temperature and pressure. In addition, when measuring liquids, the span error can be reduced by using the density of a liquid with a similar density, such as water.

Furthermore, the above formula (13) indicates that as density ρ increases, frequency f decreases. Furthermore, as density measurement coefficient Cd increases, the change in frequency f relative to a change in density ρ decreases.

From the above, the relationship between the density measurement coefficient Cd and the stiffness K is expressed by the following equation (14).

(1-3-3. Operation of Coriolis Mass Flowmeter (1))
The operation of the Coriolis mass flowmeter (1) will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of a measurement process of the Coriolis mass flowmeter (1) according to the embodiment. As shown in Fig. 3, the Coriolis mass flowmeter (1) has a detection unit (10) and a conversion unit (20). The detection unit (10) also has an excitation unit (12), an upstream sensor (13), a downstream sensor (14), and a temperature sensor (15). The conversion unit (20) also has a drive control unit (21) including an amplitude calculation unit (21a), an amplitude control unit (21b), a multiplier (21c), an excitation circuit (21d), and a current amplitude calculation unit (21e), a mass flow calculation unit (22), a density calculation unit (23), a phase difference calculation unit (24a), a frequency calculation unit (24b), an amplitude calculation unit (24c), an amplitude calculation unit (24d), a temperature calculation unit (24e), and a pressure selection switch (24f).

First, the upstream sensor (13) of the detection unit (10) outputs an upstream signal S1 (13a). Also, the downstream sensor (14) of the detection unit (10) outputs a downstream signal S2 (14a).

Next, the drive control unit (21) of the conversion unit (20) controls the excitation signal drive (12a) so that the amplitude of the upstream signal S1 (13a) becomes the amplitude target value (27c). Here, the amplitude calculation unit (21a) outputs the amplitude of the upstream signal S1 (13a). The amplitude control unit (21b) calculates the drive gain (27b) from the amplitude calculated by the amplitude calculation unit (21a) and the amplitude target value (27c). At this time, P control, PI control, etc. are used. The multiplier (21c) multiplies the upstream signal S1 (13a) by the drive gain (27b) to calculate a control signal. The excitation circuit (21d) creates the excitation signal drive (12a) from the control signal. Then, the excitation unit (12) of the detection unit (10) is driven by the excitation signal drive (12a). At this time, the excitation unit (12) converts the current into force. In addition, the current amplitude calculation unit (21e) outputs the amplitude of the current value output by the excitation circuit (21d) as the drive current (27a).

In the example shown in FIG. 3, amplitude control is performed using the upstream signal S1 (13a), but amplitude control can also be performed using the downstream signal S2 (14a). It is also possible to use both the upstream signal S1 (13a) and the downstream signal S2 (14a).

The amplitude calculation unit (24c) of the conversion unit (20) outputs the amplitude S1 (27d) of the upstream signal S1 (13a). The amplitude calculation unit (24d) outputs the amplitude S2 (27e) of the downstream signal S2 (14a). The amplitude calculation units (24c, 24d) can also perform output processing at the same time as the phase difference calculation using a Hilbert transform or the like. The phase difference calculation unit (24a) of the conversion unit (20) calculates the phase difference θ (28d) from the upstream signal S1 (13a) and the downstream signal S2 (14a). The frequency calculation unit (24b) of the conversion unit (20) calculates the frequency f (28c) from at least one of the upstream signal S1 (13a) and the downstream signal S2 (14a). The temperature calculation unit (24e) of the conversion unit (20) calculates the temperature T (28e) from the temperature signal T (15a).

The mass flow calculation unit (22) of the conversion unit (20) calculates the mass flow rate Qm (28a) from the phase difference θ (28d) and the frequency f (28c) using the above-mentioned formula (2). The mass flow calculation unit (22) calculates the mass flow rate Qm (28a) using the flow measurement coefficient Cq (28f). Here, the mass flow rate Qm (28a) depends on temperature, pressure, and density. Since the Coriolis mass flow meter (1) cannot measure pressure, an external pressure gauge (29) is attached to obtain the external input pressure Pin (28r) or set the default pressure Ps (28q). When the pressure gauge (29) is connected, the pressure gauge connection signal (28s) is set. The pressure selection switch (24f) outputs the external input pressure Pin (28r) or the default pressure Ps (28q) according to the pressure gauge connection signal (28s), and sets it as the pressure P (28t). At this time, the mass flow calculation unit (22) corrects the mass flow Qm (28a) using the flow measurement correction coefficient (28g) and at least one of the temperature T (28e), density ρ (28b), and pressure P (28t).

The density calculation unit (23) of the conversion unit (20) calculates the density ρ (28b) from the frequency f (28c) using the above-mentioned formula (12). The density calculation unit (23) calculates the density ρ (28b) using the density measurement coefficient Cd (28k) and the density measurement coefficient fa (28l). Here, the density ρ (28b) depends on the temperature and pressure. At this time, the density calculation unit (23) corrects the density ρ (28b) using the density measurement correction coefficient (28m) and at least one of the temperature T (28e) and the pressure P (28t). Note that this correction is not a correction for a change in the measurement target, but a correction for a situation in which the above-mentioned formula (9) does not hold due to a change in the rigidity of the vibration tube (11). The density calculation unit (23) corrects the frequency to a specified state, such as 20°C and 1 atmosphere.

The conversion unit (20) stores all of the coefficients, setting values, and measurement results used in the above-mentioned calculations as control parameters (27) and parameters (28). The calibration control unit (40) and diagnosis control unit (60) operate by reading and setting the values of these parameters.

(1-4. Issues with the prior art)
Below, the problems with the conventional technology will be described in the order of stiffness damping diagnosis processing, corrosion diagnosis processing, density calibration processing, flow rate calibration processing, and prediction processing for maintenance, etc.

(1-4-1. Stiffness Damping Diagnosis Processing and Corrosion Diagnosis Processing)
Conventional stiffness attenuation diagnostic processing and corrosion diagnostic processing use amplitude information, so they are affected by the amplification sensitivity of the drive circuit and measurement circuit. In addition, conventional processing performs diagnosis using input and output signals of the converter, so it includes unmeasurable characteristics such as changes in magnetic flux density of the magnets of the driver and pick-off and gain of the circuit. Therefore, conventional processing cannot measure the absolute value of the stiffness of the vibration tube, and determines the relative value.

In addition, the conventional process measures amplitude, so it is subject to the effects of vibration, temperature, and the like. Here, the mass flow rate and density of the Coriolis mass flowmeter are measured from the phase difference and frequency, and the accuracy of the amplitude measurement is low. Furthermore, in the conventional process, the drive gain is fixed and a special mechanism is required for the converter, such as measuring the rate of change of the amplitude, so in addition to the normal mass flow rate and density measurement, a heavy load calculation is required. In addition, in the conventional process, corrosion is determined by stiffness, and thickness change is not directly obtained. Here, the cause of stiffness change is not limited to corrosion. The density error diagnosis process and thickness stiffness diagnosis process executed by the diagnosis system (1000) contribute to solving the above problems.

(1-4-2. Density calibration process)
In conventional density calibration processing, changing parameters creates discontinuity in the measurement results. This becomes a factor of variation, particularly when calibration is performed frequently. Furthermore, even with conventional processing, it is possible to calculate density error from the difference with the known density of the fluid used for calibration at the time of calibration, but the density error depends on the density of the object to be measured. Here, since the purpose of a Coriolis mass flowmeter is to measure mass flow rate and density, it is necessary to grasp the density error in order to guarantee performance. The density calibration processing and density error diagnosis processing executed by the diagnosis system (1000) contribute to solving the above problems.

(1-4-3. Flow rate calibration process)
Conventional flow rate calibration processes require a device that provides a known flow rate or a reference mass flow meter, and the calibration device is large-scale. In addition, in conventional processes, mass flow rate calibration requires removing the device and transporting it to a calibration facility for calibration, which results in a large amount of cost and time when the flow meter cannot be used. Since measurement accuracy is important, calibration is performed during regular maintenance. In conventional processes, there are attempts to calibrate Coriolis mass flow meters at the site of use, but this requires a compact flow rate calibration device. Here, since the purpose of the Coriolis mass flow meter is to measure mass flow rate and density, it is necessary to grasp the flow rate error in order to guarantee performance. The flow rate error diagnosis and simple correction process performed by the diagnostic system (1000) contributes to solving the above problems.

(1-4-4. Prediction processing of maintenance, etc.)
Conventional maintenance and replacement timing prediction processes predict timing based on stiffness or damping. It is difficult to determine the value that requires maintenance based on these parameters alone. The timing prediction diagnostic process executed by the diagnostic system (1000) contributes to solving the above problem.

(1-5. Effects of diagnostic system (1000))
In the following, the effects of the diagnostic system (1000) will be described in the order of density error diagnostic processing, thickness stiffness diagnostic processing, flow rate error diagnostic/simple correction processing, and timing prediction diagnostic processing.

(1-5-1. Density Error Diagnosis Processing and Thickness Stiffness Diagnosis Processing)
As described above, in the diagnostic system (1000), the diagnostic device (2) generates a density diagnostic result regarding the density error of the fluid before and after the density calibration based on a density calibration result regarding the calibration of the density of the fluid generated by calibrating the Coriolis mass flowmeter (1) that measures the flow rate and density of the fluid flowing through the vibrating tube (11) based on the Coriolis force acting on the vibrating tube (11), and performs a calculation regarding at least one of the thickness and rigidity of the vibrating tube (11) based on the density diagnostic result to generate a thickness and rigidity diagnostic result regarding the change in the vibrating tube (11). The diagnostic device (2) also calculates the density error using the initial density measurement coefficient, the density measurement coefficient indicated by the density calibration result, and the density of the measurement target, and generates a thickness and rigidity diagnostic result including at least one of the results regarding the thickness change and rigidity change of the vibrating tube (11) using the rate of change of the density measurement coefficient indicated by the density calibration result and the design value of the vibrating tube (11), and detects an abnormality regarding the vibrating tube (11) when the thickness and rigidity diagnostic result is equal to or greater than a threshold value. Furthermore, the diagnostic device (2) generates a thickness/rigidity diagnostic result including at least one of the inner diameter, wall thickness, wall thickness change, wall thickness change rate, rigidity change rate, corrosion diagnosis, and adhesion diagnosis of the vibration pipe (11).

As a result, the diagnostic system (1000) can determine corrosion of the oscillating tube without using amplitude information that is affected by the amplification sensitivity of the drive circuit or measurement circuit, and can accurately diagnose the condition of the oscillating tube of the Coriolis mass flowmeter (1). In addition, the diagnostic system (1000) can also directly determine changes in the wall thickness of the oscillating tube, making it easy to diagnose malfunctions and performance degradation of the Coriolis mass flowmeter (1).

(1-5-2. Flow rate error diagnosis and simple correction process)
As described above, in the diagnostic system (1000), the diagnostic device (2) performs calculations on the flow rate of the fluid based on the thickness/rigidity diagnostic result, and generates a flow rate diagnostic result on the flow rate error of the fluid. The diagnostic device (2) also calculates a flow rate correction coefficient using at least one of the stiffness change rate, the thickness change rate, and the change rate of the density measurement coefficient, and performs update control of the flow rate correction coefficient used by the Coriolis mass flowmeter (1) to measure the flow rate based on the calculated flow rate correction coefficient. Therefore, in the diagnostic system (1000), the mass flow rate can be simply corrected from stiffness change, thickness change, density measurement coefficient change, etc., without calibrating the mass flow rate in a calibration facility.

(1-5-3. Timing Prediction Diagnosis Processing)
As described above, in the diagnostic system (1000), the diagnostic device (2) predicts the occurrence of a fault in the Coriolis mass flowmeter (1), the time required for maintenance or equipment replacement, the operating time, or the integrated flow rate of the fluid based on the density calibration result, the density diagnosis result, the wall thickness/rigidity diagnosis result, or the flow rate diagnosis result, and generates these as timing prediction diagnostic results. Therefore, in the diagnostic system (1000), by using either the result of the calibration process or the result of each diagnostic process, it is possible to more accurately and easily predict the timing of maintenance, etc.

2. Configuration of each device in the diagnostic system (1000)
The functional configuration of each device of the diagnostic system (1000) shown in FIG. 1 will be described with reference to FIG. 4. FIG. 4 is a block diagram showing an example of the configuration of each device of the diagnostic system according to the embodiment. Below, an example of the configuration and processing of the diagnostic system (1000) as a whole will be described, and then an example of the configuration of the diagnostic device (2) will be described. In FIG. 4, the solid arrows indicate information such as signals, and the dashed arrows indicate triggers for processing.

(2-1. Example of the overall configuration of the diagnostic system (1000))
As shown in Fig. 4, the diagnostic system (1000) has a Coriolis mass flowmeter (1), a diagnostic device (2), and a calibration device (3). In Fig. 4, the Coriolis mass flowmeter (1), the diagnostic device (2), and the calibration device (3) are shown as separate devices, but two or three of the above three devices may be integrated into one configuration. Note that the configuration and processing of the Coriolis mass flowmeter (1) are common to the configuration and processing of the Coriolis mass flowmeter (1) described in (1-3-1. Basic configuration of the Coriolis mass flowmeter (1)), and therefore will not be described here.

The configuration and processing overview of the calibration control unit (40) of the calibration device (3) are the same as those of the external device (31) or the calibration control unit (40) in the conversion unit (20) of the Coriolis mass flowmeter (1) described in (1-3-1. Basic configuration of the Coriolis mass flowmeter (1)), so a detailed description is omitted. However, the configuration and processing details of the calibration control unit (40) will be described later in [3. Details of each process of the calibration device (3) and the diagnosis device (2)].

(2-2. Overall Processing of the Diagnostic System (1000))
As shown in Fig. 4, the calibration device (3) executes density calibration processing by the density calibration unit (51). The diagnosis device (2) executes diagnosis processing in the following order: density error diagnosis processing by the density error diagnosis unit (61), thickness stiffness diagnosis processing by the thickness stiffness diagnosis unit (70), flow rate error diagnosis and simple correction processing by the flow rate error diagnosis simple correction unit (80), and timing prediction diagnosis processing by the timing prediction diagnosis unit (90). That is, in the diagnosis system (1000), the diagnosis device (2) executes each diagnosis from the change in the density measurement coefficient obtained by the density calibration unit (51) as shown below.

(2-2-1. Density calibration process)
As the first process, the density calibration process will be described. First, the density calibration unit (51) of the calibration device (3) outputs the density calibration result (151) and updates the density measurement coefficient Cd (28k) and the density measurement coefficient fa (28l). The density calibration unit (51) also measures the frequency f (28c) of the measurement object whose density is known, and obtains the density measurement coefficient. The density calibration unit (51) also uses only the density of the measurement object and the frequency f (28c) obtained by the frequency calculation unit (24b) of the Coriolis mass flowmeter (1). The density calibration unit (51) then sets a density calibration completion signal (160) at the end of execution. The mass flow calibration unit (41) of the calibration device (3) measures the frequency f (28c) and the phase difference θ (28d) at a known flow rate, and obtains the flow measurement coefficient Cq (28f). Then, the mass flow rate calibration unit (41) sets a flow rate calibration completion signal (120) when the process is completed.

(2-2-2. Density Error Diagnosis Processing)
As the second process, the density error diagnosis process will be described. First, the density error diagnosis unit (61) of the diagnosis device (2) executes the process when the density calibration completion signal (160) is set. At this time, the density error diagnosis unit (61) executes the density error diagnosis process from the change in the density measurement coefficient included in the density calibration result (151). The density error diagnosis unit (61) also stores the process result in the density diagnosis result (201). Then, when the process ends, the density error diagnosis unit (61) resets the density calibration completion signal (160) and sets the density diagnosis completion signal (210).

(2-2-3. Thickness and rigidity diagnosis process)
As the third process, the thickness/rigidity diagnosis process will be described. First, the thickness/rigidity diagnosis unit (70) of the diagnosis device (2) executes the process when the density diagnosis completion signal (210) is set. At this time, the thickness/rigidity diagnosis unit (70) obtains the rate of change of thickness and rigidity from the change in the density measurement coefficient, and performs diagnosis. The thickness/rigidity diagnosis unit (70) also stores the processing result in the thickness/rigidity diagnosis result (301). Then, the thickness/rigidity diagnosis unit (70) resets the density diagnosis completion signal (210) when the process is completed. The thickness/rigidity diagnosis completion signal (310) is set.

(2-2-4. Flow rate error diagnosis and simple correction process)
As the fourth process, the flow error diagnosis and simple correction process will be described. First, the flow error diagnosis simple correction unit (80) of the diagnosis device (2) executes the process when the thickness stiffness diagnosis completion signal (310) or the flow calibration completion signal (120) is set. At this time, the flow error diagnosis simple correction unit (80) reduces the flow error and diagnoses the flow error by updating the flow correction coefficient fk (28u) based on the change in the density measurement coefficient, the change in the thickness, the change in the stiffness, etc. In addition, the flow error diagnosis simple correction unit (80) saves the process result in the flow diagnosis result (501). When the process is completed, the flow error diagnosis simple correction unit (80) resets the thickness stiffness diagnosis completion signal (310) and the flow calibration completion signal (120).

(2-2-5. Timing Prediction Diagnosis Processing)
As the fifth process, a timing prediction diagnosis process will be described. First, the timing prediction diagnosis unit (90) of the diagnosis device (2) predicts the time when the target value will be reached by using the density calibration result (151), density diagnosis result (201), thickness stiffness diagnosis result (301), or flow rate diagnosis result (501). At this time, the timing prediction diagnosis unit (90) sets a threshold value to predict the time required until a failure occurs or a state where maintenance is required, the operating time, or the accumulated flow rate of the fluid.

(2-3. Configuration example of diagnostic device (2))
An example of the configuration of the diagnostic device (2) according to the embodiment will be described below. As shown in Fig. 4, the diagnostic device (2) has a diagnostic control unit (60), a transmitting/receiving unit (200), and a notification unit (300). The diagnostic device (2) may also have an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the diagnostic device (2), and a display unit (e.g., a liquid crystal display, etc.) that displays various information.

(2-3-1. Diagnosis Control Unit (60))
The diagnostic control unit (60) is realized, for example, by a central processing unit (CPU), a micro processing unit (MPU), etc., executing various programs (corresponding to an example of an information processing program) stored in a storage device inside the diagnostic device (2) using a RAM as a working area. The diagnostic control unit (60) is also realized, for example, by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

As shown in FIG. 4, the diagnosis control unit (60) has a density error diagnosis unit (61), a wall thickness rigidity diagnosis unit (70), a flow rate error diagnosis simple correction unit (80), and a timing prediction diagnosis unit (90), and realizes or executes the functions and actions of the information processing described below. Note that the internal configuration of the diagnosis control unit (60) is not limited to the configuration shown in FIG. 4, and may be other configurations as long as they perform the information processing described below. Also, the connection relationships of the processing units in the diagnosis control unit (60) are not limited to the connection relationships shown in FIG. 4, and may be other connection relationships.

(2-3-1-1. Density Error Diagnosis Unit (61))
The density error diagnosis unit (61) generates a density diagnosis result (201) relating to the density error of the fluid before and after the density calibration based on a density calibration result (151) relating to the calibration of the density of the fluid generated by calibrating a Coriolis mass flowmeter (1) that measures the flow rate and density of the fluid flowing through the vibrating tube (11) based on the Coriolis force acting on the vibrated vibrating tube (11).

For example, the density error diagnosis unit (61) calculates the density error Δρ0 using the initial density measurement coefficients (Cd0, fa0), the density measurement coefficients (Cdc, fac) indicated by the density calibration result, and the density ρt of the object to be measured. The density error diagnosis unit (61) also calculates the rate of change (aCd, afa) of the density measurement coefficients using the initial density measurement coefficients (Cd0, fa0), the density measurement coefficients (Cdc, fac) indicated by the density calibration result, and the density ρt of the object to be measured.

Furthermore, the density error diagnosis unit (61) calculates the density fluctuation Δρ0 that occurs when the density measurement coefficient is updated using the density measurement coefficient (Cd0, fa0) before the change, the density measurement coefficient (Cdc, fac) indicated by the density calibration result, and the density ρt of the measurement target, and detects an abnormality related to the vibrating tube (11) if the density fluctuation exceeds an allowable value.

(2-3-1-2. Thickness and rigidity diagnosis unit (70))
The thickness and stiffness diagnosis unit (70) performs calculations on at least one of the thickness and stiffness of the vibration tube (11) based on the density calibration result (151) and generates a thickness and stiffness diagnosis result (301) on the change of the vibration tube (11). For example, the thickness and stiffness diagnosis unit (70) uses the change rate (aCd, afa) of the density measurement coefficient indicated by the density calibration result (151) or the density diagnosis result (201) and the design values (vibration tube inner diameter d, vibration tube outer diameter D) of the vibration tube (11) to generate a thickness and stiffness diagnosis result (301) including at least one of the results on the change of the thickness and stiffness of the vibration tube (11), and detects an abnormality related to the vibration tube (11) when the thickness and stiffness diagnosis result (301) is equal to or greater than a threshold value. In addition, the thickness/rigidity diagnosis unit (70) generates a thickness/rigidity diagnosis result (301) including at least one of the inner diameter dc, the thickness tc, the thickness change dt, the thickness change rate rt, and the rigidity change rate aK of the vibration pipe (11).

Furthermore, the thickness/rigidity diagnosis unit (70) uses the results regarding the thickness and rigidity changes of the vibrating tube (11) to perform a fault diagnosis of the Coriolis mass flowmeter (1), including at least one of a thickness diagnosis, a rigidity diagnosis, a corrosion diagnosis, and an adhesion diagnosis, and detects a fault in the Coriolis mass flowmeter (1) if the above results exceed an alarm value.

(2-3-1-3. Flow Error Diagnosis Simplified Correction Unit (80))
The flow rate error diagnosis simple correction unit (80) performs calculations related to the flow rate of the fluid based on the thickness/rigidity diagnosis result (301) and generates a flow rate diagnosis result (501) related to the flow rate error of the fluid. For example, the flow rate error diagnosis simple correction unit (80) calculates a flow rate correction coefficient fkq using at least one of the stiffness change rate aK, the thickness change rate dt, and the change rate adc of the density measurement coefficient, and performs update control of the flow rate correction coefficient used by the Coriolis mass flowmeter (1) to measure the flow rate based on the calculated flow rate correction coefficient fkq.

At this time, the flow error diagnosis simple correction unit (80) uses the flow correction coefficient fk before the change and the calculated flow correction coefficient fkq to calculate the flow rate fluctuation rate rqd when the flow correction coefficient is updated, and if the flow rate fluctuation rate exceeds the allowable value, updates the flow measurement coefficient used by the Coriolis mass flowmeter (1) to measure the flow rate. In addition, the flow error diagnosis simple correction unit (80) can also determine in advance the type of rate of change and the weighting coefficient used to calculate the flow correction coefficient fkq from the results of a simulation or experiment.

(2-3-1-4. Timing Prediction Diagnosis Unit (90))
The timing prediction diagnosis unit (90) predicts the occurrence of a fault in the Coriolis mass flowmeter (1), the time required for maintenance or equipment replacement, the operating time, or the accumulated flow rate of the fluid based on the density calibration result (151), the density diagnosis result (201), the wall thickness/rigidity diagnosis result (301), or the flow rate diagnosis result (501), and generates the result as a timing prediction diagnosis result (603).

For example, the timing prediction diagnosis unit (90) uses at least one of the calculated density measurement coefficient (Cdc, fac), density measurement coefficient change rate (aCdc, afac), and density error Δρ0 as the density diagnosis result (201) and outputs it as the timing prediction diagnosis result (603). The timing prediction diagnosis unit (90) also uses at least one of the inner diameter dc, thickness tc, thickness change dt, and thickness change rate rt of the vibration tube (11) as the thickness stiffness diagnosis result (301) and outputs it as the timing prediction diagnosis result (603). The timing prediction diagnosis unit (90) also uses at least one of the flow correction coefficient fkq and flow error rate rqe as the flow rate diagnosis result (501) and outputs it as the timing prediction diagnosis result (603).

The timing prediction diagnosis unit (90) also finds an approximate straight line or an approximate curve that indicates the change over time of the parameters included in the density calibration result (151), density diagnosis result (201), thickness stiffness diagnosis result (301) or flow rate diagnosis result (501), the change over operation time of the parameter, or the change over the cumulative flow rate of the parameter, and predicts the time, operation time, or cumulative flow rate of the fluid until the approximate straight line or approximate curve reaches a diagnostic target value specified as a state in which a fault has occurred and maintenance or equipment replacement is required, and outputs this as a timing prediction diagnosis result (603).

(2-3-2. Transmitter/receiver unit (200))
The transmitting/receiving unit (200) is realized by, for example, a network interface card (NIC) or the like. For example, the transmitting/receiving unit (200) acquires a density calibration result (151) from a calibration device (3). The transmitting/receiving unit (200) is connected to a predetermined communication network by wire or wirelessly, and transmits and receives information between various devices.

(2-3-3. Notification Department (300))
The notification unit (300) notifies of an abnormality related to the vibrating pipe (11) when the density calibration result (151), the density diagnosis result (201), the wall thickness/rigidity diagnosis result (301) or the flow rate diagnosis result (501) exceeds a predetermined alarm value.

[3. Details of each process of the calibration device (3) and the diagnosis device (2)]
5 to 26 and equations, the details of each process of the calibration device (3) and diagnosis device (2) according to the embodiment will be described. The following describes the density calibration diagnosis process of the calibration device (3), the thickness stiffness diagnosis process of the diagnosis device (2), the flow rate error diagnosis and simple correction process, and the timing prediction diagnosis process in that order.

(3-1. Density calibration process)
The density calibration process executed by the density calibration unit (51) of the calibration device (3) according to the embodiment will be described with reference to Figures 5 and 6 and equations. Below, the theoretical equation of the density calibration process will be explained, followed by the overall density calibration process and the density calibration coefficient calculation process.

(3-1-1. Theoretical formula for density calibration process)
The theoretical formula for the density calibration process will be explained below. The density measurement coefficient Cd (28k) and the density measurement coefficient fa (28l) are calibrated using fluids with two or more known densities. The above-mentioned formula (12) is considered to be a linear formula. If the coefficients after calibration are the density measurement coefficient Cdc and the density measurement coefficient fac, then the following formulas (15) to (18) are obtained.

Now consider calibration at two points. If the frequency in a material with density ρ1 is f1 and the frequency in a material with density ρ2 is f2, then we obtain the following equations (19) and (20). Here, we assume that frequency f1 and frequency f2 have been corrected so that the above-mentioned equation (9) holds.

Calculating coefficients a and b gives us the following equations (21) and (22).

The density measurement coefficient Cdc and density measurement coefficient fac are calculated using the following equations (23) and (24).

When calibrating at three or more points, create the above formula (15) for each result and use the least squares method or other methods to find the coefficients.

(3-1-2. Overall density calibration process)
The overall process of the density calibration process will be described with reference to Fig. 5 and Fig. 6. Fig. 5 is a diagram showing an example of the overall process of the density calibration process according to the embodiment. The configuration and process of the density calibration unit (51) of the calibration device (3) will be described below.

The configuration and processing of the density calibration unit (51) will be described with reference to FIG. 5. As shown in FIG. 5, the density calibration unit (51) has a density measurement coefficient calculation unit (52). The density measurement coefficient calculation unit (52) outputs a density calibration result (151) from the parameters (28) and the density calibration set value (152). The density measurement coefficient calculation unit (52) also sets a density calibration completion signal (160). Here, the density calibration completion signal (160) is used to execute the density error diagnosis unit (61) and is reset within the density error diagnosis unit (61) of the diagnosis device (2).

The density measurement coefficient calculation unit (52) sets the density calibration result (151) in the parameter (28). The density error diagnosis unit (61) described below determines whether or not the result can be set, and sets the result in the parameter (28). If the density error diagnosis unit (61) is to be used, no setting is made here.

(3-1-3. Density measurement coefficient calculation process)
The density measurement coefficient calculation process by the density measurement coefficient calculation unit (52) of the density calibration unit (51) will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the density calibration process according to the embodiment. As shown in Fig. 6, the density measurement coefficient calculation unit (52) has a frequency correction unit (53), a material selection switch (54), a standard density calculation unit (55), a density selection switch (56), a material selection switch (57), and a density measurement coefficient calculation execution unit (58).

Here, the manually input density ρin (152a) indicates a density value manually input by the display operation unit (30) or the external device (31). Also, the density selection (152b) indicates a signal that controls the density selection switch (56), and selects the standard density ρc (156) or the manually input density ρin (152a). The coefficient n (152c) indicates the number of the measured substance.

The frequency correction unit (53) corrects the frequency f (28c) using the density measurement correction coefficient (28m), temperature T (28e), and pressure P (28t), and outputs the corrected frequency fn (153). This correction is not for changes in the measurement object, but for a situation in which the above-mentioned equation (9) does not hold due to changes in the rigidity of the vibration tube (11), etc. The frequency correction unit (53) corrects the frequency to a specified state, such as 20°C and 1 atm. This process is the same as the process included in the density calculation unit (23).

The material selection switch (54) outputs the corrected frequency f1 (154) or the corrected frequency f2 (155) according to the coefficient n (152c). The standard density calculation unit (55) calculates the standard density ρc (156) from the temperature T (28e), the pressure P (28t) and the coefficient n (152c). The standard density calculation unit (55) operates when a density calculation formula corresponding to the target material is prepared. The density selection switch (56) selects the standard density ρc (156) or the manually input density ρin (152a) according to the density selection (152b) to obtain the density ρn (157). The material selection switch (57) outputs the density ρ1 (158) or the density ρ2 (159) according to the coefficient n (152c).

The density measurement coefficient calculation execution unit (58) uses the corrected frequency f1 (154), the corrected frequency f2 (155), the density ρ1 (158), and the density ρ2 (159) to calculate the density measurement coefficient Cdc (151a) and the density measurement coefficient fac (151b) according to the above-mentioned equations (21) to (24).

The density measurement coefficient calculation unit (52) also stores the date and time (28x) in the calibration date and time (151x). Here, the date and time (28x) is the time held by the conversion unit (20) or the external device (31) and is the date and time when the calibration was performed. The density measurement coefficient calculation unit (52) also stores the conversion unit drive time (28y) in the drive time (151y). Here, the conversion unit drive time (28y) is held by the conversion unit (20) and indicates a value obtained by integrating the drive time of the conversion unit (20). The density measurement coefficient calculation unit (52) also stores the integrated flow rate (28z) in the integrated flow rate (151z). Here, the integrated flow rate (28z) is held by the conversion unit (20) and indicates a value obtained by integrating the mass flow rate.

When the density measurement coefficient calculation unit (52) ends the density measurement coefficient calculation process, it sets the update flag (151s) and the density calibration completion signal (160). The update flag (151s) is used by the timing prediction diagnosis unit (90).

(3-2. Density Error Diagnosis Processing)
7 to 10 and equations, the density error diagnosis process executed by the density error diagnosis unit (61) of the diagnosis device (2) according to the embodiment will be described. Below, the theoretical equation of the density error diagnosis process will be explained, followed by the overall density error diagnosis process, the initialization determination process, the density error initialization process, and the density error calculation determination process, in that order.

(3-2-1. Theoretical formula for density error diagnosis processing)
The theoretical formula of the density error diagnosis process will be described below. First, the density fluctuation Δρ (201c) is calculated from the changes in the density measurement coefficient Cd (28k) and the density measurement coefficient fa (28l). Here, the density measurement coefficients obtained by density calibration are the density measurement coefficient Cdc (151a) and the density measurement coefficient fac (151b). In addition, the density measurement coefficients before calibration are the density measurement coefficient Cd (28k) and the density measurement coefficient fa (28l). From the above-mentioned formula (13), when a material with a measurement target density ρt (202c) is measured in a calibrated state, the frequency f is given by the following formula (25).

An error occurs when calculating density using frequency f and the pre-calibration coefficients, density measurement coefficient Cd (28k) and density measurement coefficient fa (28l). If the density including the error is ρe, then we get the following equation (26).

The density variation Δρ (201c) when the density measurement coefficient is changed can be calculated using the following formula (27).

The density variation Δρ (201c) depends on the measured density ρt (202c). It indicates the density error that has occurred since the last density calibration.

Changing the density measurement coefficient creates discontinuities in the density measurement results. If the density fluctuation Δρ (201c) is within the allowable range, there is also the option of prioritizing the continuity of the measurement values. The density fluctuation allowable value (202d) is set as the variable ρlim, and is compared with the absolute value of the density fluctuation Δρ (201c) to determine whether or not the density measurement coefficient can be replaced, thereby suppressing fluctuations in the density measurement results. In this case, the conditional formula is the following formula (28).

When the density measurement coefficient is replaced, an alarm can be set. In addition, the density variation Δρ (201c) can be displayed on the display operation unit (30) or an external device (31), and it is also possible to input whether or not the density measurement coefficient should be replaced.

The density measurement coefficients in the initial state, such as at the time of shipment, are stored and designated as the initial coefficients Cd0 (202a) and fa0 (202b). The density error Δρ0 (201d) from the initial state is calculated as in the following formula (29).

When the absolute value of the density error Δρ0 (201d) becomes equal to or greater than the density error warning value (202h), a density error abnormality (201h) is set. The density error warning value (202h) is set as the variable ρ0lim. In this case, the condition formula is the following formula (30).

By setting a density error anomaly (201h) due to an error from the initial value, the user is notified of an abnormality in the device. The occurrence of a density error indicates that an error has also occurred in the mass flow measurement results. The density error anomaly (201h) notifies the user that readjustment of the measuring device is necessary.

The coefficient change rate aCd (201e) is calculated from the initial coefficient Cd0 (202a) and the density measurement coefficient Cdc (151a) as shown in the following formula (31).

The coefficient change rate afa (201f) is calculated from the initial coefficient fa0 (202b) and the density measurement coefficient fac (151b) as shown in the following formula (32).

The change from the previous calibration can be calculated using the density measurement coefficient Cd and density measurement coefficient fa from the previous calibration.

Abnormality diagnosis is performed from the rate of change of the density measurement coefficient. It is determined whether the coefficient change rate aCd (201e) is greater than the coefficient change rate aCd tolerance (202i). The coefficient aCdlim indicates the coefficient change rate aCd tolerance (202i). If it is greater, a coefficient change rate aCd abnormality (201i) is set. If there is no change, the coefficient change rate aCd (201e) becomes the value 1.0. It is also possible to determine an upper and lower limit for the judgment. In this case, the condition formula is the following formula (33).

It is determined whether the coefficient change rate afa (201f) is greater than the coefficient change rate afa tolerance value (202j). The coefficient afalim indicates the coefficient change rate afa tolerance value (202j). If it is greater, a coefficient change rate afa abnormality (201j) is set. If there is no change, the coefficient change rate afa (201f) becomes the value 1.0. It is also possible to determine upper and lower limits for the determination. In this case, the condition formula is the following formula (34).

(3-2-2. Overall Density Diagnostic Processing)
The overall process of the density error diagnosis process will be described with reference to Fig. 7. Fig. 7 is a diagram showing an example of the overall process of the density error diagnosis process according to the embodiment. The configuration of the density error diagnosis unit (61) of the diagnosis device (2) will be described below.

As shown in FIG. 7, the density error diagnosis unit (61) is part of the diagnosis control unit (60) and executes processing when the density calibration completion signal (160) is set. The density error diagnosis unit (61) also has an initialization determination unit (62), a density error initialization unit (63), and a density error calculation determination unit (64). The density calibration unit (51) updates the parameters (28) immediately after calculation, but the density error diagnosis unit (61) determines whether to update based on the density fluctuation Δρ (201c).

The initialization determination unit (62) selects the process to be executed based on the density calibration completion signal (160) and the density diagnosis setting value (202). At this time, if initialization is required, the initialization determination unit (62) sets the initialization signal (203) to execute the density error initialization unit (63). On the other hand, if initialization is not required, the initialization determination unit (62) sets the calculation determination signal (204) to execute the density error calculation determination unit (64).

The density error initialization unit (63) initializes the density diagnosis setting value (202) and the density diagnosis result (201). Then, the density error initialization unit (63) resets the density calibration completion signal (160) at the end of processing, and sets the density diagnosis completion signal (210).

The density error calculation and determination unit (64) updates the density diagnosis result (201) and updates the density calibration coefficient of the parameter (28). Then, the density error calculation and determination unit (64) resets the density calibration completion signal (160) at the end of processing and sets the density diagnosis completion signal (210).

(3-2-3. Initialization Determination Process)
The initialization judgment process by the initialization judgment unit (62) of the density error diagnosis unit (61) will be described with reference to FIG. 8. FIG. 8 is a diagram showing an example of density error diagnosis process 1 according to the embodiment. As shown in FIG. 8, the initialization judgment unit (62) executes the process when the density calibration completion signal (160) is set. The initialization judgment unit (62) also outputs an initialization signal (203) and a calculation judgment signal (204) based on the initial coefficient Cd0 (202a), the initial coefficient fa0 (202b), the initialization execution command (202u) and the initial date and time (202x) as the density diagnosis set value (202). The flow of the initialization judgment process will be described later in [5. Flow of each process of the calibration device (3) and the diagnosis device (2)].

(3-2-4. Density error initialization process)
The density error initialization process performed by the density error initialization unit (63) of the density error diagnosis unit (61) will be described with reference to Fig. 9. Fig. 9 is a diagram showing an example of density error diagnosis process 2 according to the embodiment.

The density error initialization unit (63) stores the density calibration result (151) in the parameter (28) as shown below. That is, the density error initialization unit (63) assigns the value of the calibration date and time (151x) to the density calibration date and time (28n), the value of the drive time (151y) to the density calibration drive time (28o), the value of the integrated flow rate (151z) to the density calibration integrated flow rate (28p), the value of the density measurement coefficient Cdc (151a) to the density measurement coefficient Cd (28k), and the value of the density measurement coefficient fac (151b) to the density measurement coefficient fa (28l).

The density error initialization unit (63) uses the density calibration result (151) to set the initial value of the density diagnosis setting value (202) as shown below. That is, the density error initialization unit (63) substitutes the value of the calibration date and time (151x) into the initial date and time (202x), the value of the drive time (151y) into the initial drive time (202y), the value of the integrated flow rate (151z) into the initial integrated flow rate (202z), the value of the density measurement coefficient Cdc (151a) into the initial coefficient Cd0 (202a), and the value of the density measurement coefficient fac (151b) into the initial coefficient fa0 (202b). The density error initialization unit (63) also resets the initialization execution command (202u).

The density error initialization unit (63) initializes the density diagnosis result (201) as shown below. That is, the density error initialization unit (63) substitutes the value of the calibration date and time (151x) for the diagnosis date and time (201x), the value of the drive time (151y) for the drive time (201y), the value of the integrated flow rate (151z) for the integrated flow rate (201z), the value of the density measurement coefficient Cdc (151a) for the density measurement coefficient Cd (201a), and the value of the density measurement coefficient fac (151b) for the density measurement coefficient fa (201b). The density error initialization unit (63) also sets the density fluctuation Δρ (201c) to a value of 0.0, the density error Δρ0 (201d) to a value of 0.0, the coefficient change rate aCd (201e) to a value of 1.0, and the coefficient change rate afa (201f) to a value of 1.0. The density error initialization unit (63) also resets the density error abnormality (201h), the coefficient change rate aCd abnormality (201i), and the coefficient change rate afa abnormality (201j). The density error initialization unit (63) then sets the initialization flag (201t) to indicate that the density diagnosis result (201) has been initialized. The density error initialization unit (63) also sets the update flag (201s) to indicate that the density diagnosis result (201) has been updated.

The density error initialization unit (63) resets the density calibration completion signal (160) and waits until the next time the density calibration process is performed. The density error initialization unit (63) also sets the density diagnosis completion signal (210).

(3-2-5. Density Error Calculation and Determination Process)
The density error calculation determination process by the density error calculation determination unit (64) of the density error diagnostic unit (61) will be described with reference to Fig. 10. Fig. 10 is a diagram showing an example of density error diagnostic process 3 according to the embodiment. As shown in Fig. 10, the density error calculation determination unit (64) has a density error calculation unit (65), a density error comparator 1 (66), a coefficient selector (67), and density error comparators 2 (68a, 68b, 68c).

The density error calculation unit (65) calculates the density diagnosis result (201) from the change in the density measurement coefficient as shown below. That is, the density error calculation unit (65) calculates the density fluctuation Δρ (201c) using the above-mentioned formula (27), calculates the density error Δρ0 (201d) using the above-mentioned formula (29), calculates the coefficient change rate aCd (201e) using the above-mentioned formula (31), and calculates the coefficient change rate afa (201f) using the above-mentioned formula (32).

The density error comparator 1 (66) uses the above-mentioned equation (28) to compare the absolute value of the density fluctuation Δρ (201c) with the density fluctuation tolerance (202d). At this time, if the absolute value of the density fluctuation Δρ (201c) is greater than the density fluctuation tolerance (202d), the density error comparator 1 (66) sets the coefficient selection signal (205). On the other hand, if the absolute value of the density fluctuation Δρ (201c) is equal to or less than the density fluctuation tolerance (202d), the density error comparator 1 (66) resets the coefficient selection signal (205).

The coefficient selector (67) determines whether the coefficient selection signal (205) is set, and if the coefficient selection signal (205) is set, sets the density calibration result (151) to the parameter (28). That is, the coefficient selector (67) assigns the value of the calibration date and time (151x) to the density calibration date and time (28n), the value of the drive time (151y) to the density calibration drive time (28o), the value of the integrated flow rate (151z) to the density calibration integrated flow rate (28p), the value of the density measurement coefficient Cdc (151a) to the density measurement coefficient Cd (28k), and the value of the density measurement coefficient fac (151b) to the density measurement coefficient fa (28l).

The density error comparator 2 (68a, 68b, 68c) executes the following process. That is, the density error comparator 2 (68a) compares the change in the density error Δρ0 (201d) with the density error warning value (202h) and sets the density error abnormality (201h) using the above-mentioned formula (30). The density error comparator 2 (68b) compares the change in the coefficient change rate aCd (201e) with the coefficient change rate aCd allowable value (202i) and sets the coefficient change rate aCd abnormality (201i) using the above-mentioned formula (33). The density error comparator 2 (68c) compares the change in the coefficient change rate afa (201f) with the coefficient change rate afa allowable value (202j) and sets the coefficient change rate afa abnormality (201j) using the above-mentioned formula (34).

The density error initialization unit (63) resets the initialization flag (201t) to indicate that it has not been initialized. The density error initialization unit (63) also sets the update flag (201s) to indicate that the density diagnosis result (201) has been updated. The density error initialization unit (63) also resets the density calibration completion signal (160) and waits until the next time the density calibration process is performed. The density error initialization unit (63) also sets the density diagnosis completion signal (210).

(3-3. Thickness and rigidity diagnosis process)
11 to 16 and mathematical expressions, the thickness diagnosis process executed by the thickness stiffness diagnosis unit (70) of the diagnosis device (2) according to the embodiment will be described. In the following, the theoretical expressions of the thickness stiffness diagnosis process will be described, and then the overall thickness stiffness diagnosis process, the initialization determination process, the thickness stiffness diagnosis initialization process, the thickness stiffness calculation process, the thickness stiffness change initialization process, and the thickness stiffness change determination process will be described in that order. Finally, the thickness stiffness diagnosis process using the density calibration result (151) will be described.

(3-3-1. Theoretical formula for thickness and stiffness diagnosis processing)
The theoretical formula of the thickness stiffness diagnosis process will be described below. First, consider a vibration tube with a circular cross section, an outer diameter D, and an inner diameter d. If the density of the vibration tube is ρu, the length of the vibration tube is lu, and the number of vibration tubes is m, the mass Mu of the vibration tube itself is expressed by the following formula (35).

The wall thickness t of the vibration tube is given by the following formula (36).

The internal volume V of the vibrating tube is given by the following formula (37).

Calculating the coefficient Cd from the above formula (11) gives the following formula (38).

In the above formula (38), the first term Cda is an item that depends on the mass and internal volume of the vibration tube, and is dependent on the cross-sectional shape and material. The second term Cdb is an item that depends on the mass Mu of the accessory and the internal volume of the vibration tube. In other words, the heavier the accessory, the larger Cd.

In the Coriolis mass flowmeter (1), the amplitude becomes larger toward the tip, the kinetic energy varies depending on the distance from the fixed point, and the farther the mass is located, the greater the impact on the vibration. In order to discuss this accurately, it is necessary to consider the equivalent mass. In the above equation (38), the first term Cda of the coefficient Cd is not affected by the position as long as the shape of the vibrating tube does not change. Also, the second term Cdb is affected by the position. The vibrating tube length lu and the mass Md of the accessory are values that take into account the equivalent mass.

Let us consider a case where the inner diameter d of the vibrating tube increases uniformly due to corrosion or other reasons to become an inner diameter dc. The coefficient Cdc after the change is expressed by the following formula (39).

If the vibration conditions of the Coriolis mass flowmeter (1) do not change, there will be no change in the equivalent mass, and there will be no change in the vibration tube length lu and the mass Md of the accessories.

The relationship between the coefficient Cdc after the change and the stiffness Kc is given by the following equation (40). The frequency at which a material with density ρa is measured is fac.

The internal volume Vc of the vibrating tube can be calculated from the inner diameter dc using the following formula (41).

If the inner diameter changes, measurement errors can be eliminated by recalibrating and updating the coefficient Cdc and frequency fac.

The inner diameter dc (301c) of the vibration tube (11) after the change is calculated from the above formulas (38) and (39), and the following formula (42) is obtained. The density measurement coefficient Cd in the initial state is set as the initial coefficient Cd0 (302a). The inner diameter dc of the vibration tube (11) in the initial state is set as the initial inner diameter d0 (302c). The vibration tube density ρu (303b) is assumed to remain unchanged. The inner diameter dc (301c) of the vibration tube (11) after the change is calculated from the density measurement coefficient Cdc (151a) after the change and the initial coefficient Cd0 (302a), and the following formula (42) is obtained.

The wall thickness tc (301d) of the vibration tube (11) is calculated using the following formula (43).

The thickness change dt (301e) is given by the following formula (44).

The wall thickness change rate rt (301f) is given by the following formula (45). If there is no change, the wall thickness change rate rt (301f) is 1. It is also possible to subtract 1 and calculate only the amount of change.

The density measurement coefficient fa in the initial state is set as the initial coefficient fa0 (302b). The stiffness change rate aK of the vibration tube (11) from the initial state can be calculated from the above equations (14) and (40) using the following equation (46). Stiffness K0 indicates the initial stiffness. The stiffness change rate aK is 1 if there is no change. It is also possible to subtract 1 and calculate only the change. The stiffness change rate aK is expressed as the stiffness change rate aK (301g).

Here, by using the inner diameter d of the vibration tube (11) at the time of the previous calibration, the change from the previous calibration can be calculated.

A thickness and rigidity diagnosis is performed based on changes in thickness and rigidity. It is determined whether the absolute value of the difference between the inner diameter dc (301c) of the vibration tube (11) and the initial inner diameter d0 (302c) is greater than the inner diameter tolerance (302k). The coefficient dclim indicates the inner diameter tolerance (302k). If it is greater, an inner diameter abnormality (301k) is set. It is also possible to determine upper and lower limits for the judgment. In this case, the conditional formula is the following formula (47).

It is determined whether the absolute value of the difference between the wall thickness tc (301d) of the vibration pipe (11) and the initial wall thickness is greater than the wall thickness tolerance (302l). The coefficient tclim indicates the wall thickness tolerance (302l). If it is greater, a wall thickness abnormality (301l) is set. It is also possible to determine upper and lower limits for the determination. In this case, the condition formula is the following formula (48).

It is determined whether the absolute value of the thickness change dt (301e) is greater than the thickness change tolerance (302m). The coefficient dtlim indicates the thickness change tolerance (302m). If it is greater, a thickness change abnormality (301m) is set. It is also possible to determine upper and lower limits for the determination. In this case, the condition formula is the following formula (49).

It is determined whether the wall thickness change rate rt (301f) is greater than the wall thickness change rate tolerance (302n). The coefficient rtlim indicates the wall thickness change rate tolerance (302n). If it is greater, a wall thickness change rate abnormality (301n) is set. If there is no change, the wall thickness change rate rt (301f) becomes the value 1.0. It is also possible to determine upper and lower limits for the determination. In this case, the condition formula is the following formula (50).

It is determined whether the stiffness change rate aK (301g) is greater than the stiffness change rate tolerance (302o). The coefficient aKlim indicates the stiffness change rate tolerance (302o). If it is greater, a stiffness change rate abnormality (301o) is set. If there is no change, the stiffness change rate aK (301g) becomes the value 1.0. It is also possible to determine upper and lower limits for the judgment. In this case, the condition formula is the following formula (51).

Corrosion can be judged from the changes in thickness and rigidity. Several of the seven parameters obtained above are used. Here, an example of a judgment formula using the thickness change rate rt (301f) and rigidity change rate aK (301g) is shown in the following formula (52). When corrosion occurs, the thickness change rate rt (301f) becomes smaller than 1. The rigidity change rate aK (301g) becomes smaller than 1.

At this time, the judgment value rtcor and the judgment value aKcor are set as the corrosion judgment value (302p).

Adhesion can be determined from changes in thickness and rigidity. If the thickness increases without a change in rigidity, adhesion is likely. If adhesion is present inside the vibrating tube, the volume of the adhered portion is replaced by the adherent material from the measured fluid. Since the adherent material is heavier than air, the density measurement coefficient fac (151b) decreases by the mass, and the density measurement coefficient Cdc (151a) increases. If the tube is filled with fluid, it is affected by the density difference between the fluid and the adherent material. If a soft material adheres, there is no effect on rigidity.

Of the seven parameters calculated above, several are used. Here, an example of a determination formula using the coefficient change rate aCd (201e) and the coefficient change rate afa (201f) is shown in the following formula (53).

At this time, the judgment value aCdad and the judgment value afaad are set as the adhesion judgment value (302q).

The theoretical formula above is for a tube with a circular cross-sectional shape, but the formula can also be expanded for tubes with an elliptical or rectangular cross-sectional shape.

(3-3-2. Overall Processing of Thickness and Stiffness Diagnosis)
The entire thickness stiffness diagnosis process will be described with reference to Fig. 11. Fig. 11 is a diagram showing an example of the entire thickness stiffness diagnosis process according to the embodiment. The configuration of the thickness stiffness diagnosis unit (70) of the diagnosis device (2) will be described below.

As shown in FIG. 11, the thickness stiffness diagnosis unit (70) is part of the diagnosis control unit (60), and after executing the density error diagnosis process, diagnoses the thickness and stiffness using the density diagnosis result (201) obtained from the density error diagnosis unit (61). The thickness stiffness diagnosis unit (70) also has an initialization determination unit (71), a thickness stiffness diagnosis initialization unit (72), a thickness stiffness calculation unit (73), a thickness stiffness change initialization unit (74), and a thickness stiffness change determination unit (75), which respectively execute the initialization determination process, the thickness stiffness diagnosis initialization process, the thickness stiffness calculation process, the thickness stiffness change initialization process, and the thickness stiffness change determination process.

The thickness stiffness diagnosis unit (70) executes processing when the density diagnosis completion signal (210) is set. The thickness stiffness diagnosis unit (70) also resets the density diagnosis completion signal (210) when processing is completed, and waits for the next density calibration to be performed. The thickness stiffness diagnosis unit (70) also sets the thickness stiffness diagnosis completion signal (310). Here, the thickness stiffness diagnosis completion signal (310) indicates that the thickness stiffness diagnosis unit (70) has been performed. The flow rate error diagnosis simple correction unit (80), which will be described later, uses the stiffness and thickness changes obtained by the thickness stiffness diagnosis unit (70). By setting the thickness stiffness diagnosis completion signal (310), the flow rate error diagnosis simple correction unit (80) executes processing.

The initialization determination unit (71) determines the processing to be performed based on the thickness stiffness diagnosis setting value (302) and the density diagnosis completion signal (210), and sets the initialization signal (306), diagnosis initialization signal (307), or diagnosis execution signal (308). When the initialization determination unit (71) is executed for the first time, it sets the initialization signal (306), and the thickness stiffness diagnosis initialization processing is executed. When it is necessary to reset the reference data, the initialization determination unit (71) sets the diagnosis initialization signal (307), and the thickness stiffness calculation processing and the thickness stiffness change initialization processing are executed. During normal diagnosis, the initialization determination unit (71) sets the diagnosis execution signal (308), and the thickness stiffness calculation processing and the thickness stiffness change determination processing are executed.

The wall thickness stiffness diagnosis initialization unit (72) executes initialization processing of related parameters. The wall thickness stiffness diagnosis initialization unit (72) executes initialization processing only when the initialization signal (306) is set. The wall thickness stiffness diagnosis initialization unit (72) initializes the wall thickness stiffness diagnosis setting value (302) and the wall thickness stiffness diagnosis result (301) based on the vibration pipe design value (303) and the density diagnosis result (201). In addition, the wall thickness stiffness diagnosis initialization unit (72) sets the wall thickness stiffness diagnosis completion signal (310) and resets the density diagnosis completion signal (210).

The thickness stiffness calculation unit (73) executes a process of calculating the thickness stiffness change rate and outputting it to the thickness stiffness diagnosis result (301). At this time, the thickness stiffness calculation unit (73) uses the density diagnosis result (201), the thickness stiffness diagnosis setting value (302), and the vibration pipe design value (303). In addition, the thickness stiffness calculation unit (73) executes the process when the diagnosis initialization signal (307) or the diagnosis execution signal (308) is set.

The thickness stiffness change initialization unit (74) executes a process of resetting the initial value. The thickness stiffness change initialization unit (74) sets the thickness stiffness diagnosis result (301) obtained by the thickness stiffness calculation unit (73) to the initial value. The thickness stiffness change initialization unit (74) executes a process when the diagnosis initialization signal (307) is set. The thickness stiffness change initialization unit (74) initializes the thickness stiffness diagnosis setting value (302) and the thickness stiffness diagnosis result (301) based on the thickness stiffness diagnosis result (301), the density diagnosis result (201), and the thickness stiffness diagnosis setting value (302). In addition, the thickness stiffness change initialization unit (74) sets the thickness stiffness diagnosis completion signal (310) and resets the density diagnosis completion signal (210).

The thickness stiffness change determination unit (75) executes a process to set the thickness stiffness diagnosis result (301). At this time, the thickness stiffness change initialization unit (74) uses the thickness stiffness diagnosis result (301) and the thickness stiffness diagnosis setting value (302). The thickness stiffness change initialization unit (74) executes the process only when the diagnosis execution signal (308) is set. In addition, the thickness stiffness change initialization unit (74) sets the thickness stiffness diagnosis completion signal (310) and resets the density diagnosis completion signal (210).

As described above, the thickness/rigidity diagnosis unit (70) can perform diagnosis processing for thickness changes and rigidity changes, or can perform only one of them.

(3-3-3. Initialization Determination Process)
The initialization determination process by the initialization determination unit (71) of the thickness stiffness diagnosis unit (70) will be described with reference to FIG. 12. FIG. 12 is a diagram showing an example of the thickness stiffness diagnosis process 1 according to the embodiment. As shown in FIG. 12, the initialization determination unit (71) executes the process when the density diagnosis completion signal (210) is set. The initialization determination unit (71) also outputs an initialization signal (306), a diagnosis initialization signal (307), and a diagnosis execution signal (308) based on the initial inner diameter d0 (302c), the initial date and time (302x), and the initialization execution command (302u) as the thickness stiffness diagnosis set value (302). The flow of the initialization determination process will be described later in [5. Flow of each process of the calibration device (3) and the diagnosis device (2)].

(3-3-4. Thickness and stiffness diagnosis initialization process)
A wall thickness diagnosis initialization process by the wall thickness stiffness diagnosis initialization unit (72) of the wall thickness stiffness diagnosis unit (70) will be described with reference to Fig. 13. Fig. 13 is a diagram showing an example of the wall thickness stiffness diagnosis process 2 according to the embodiment. As shown in Fig. 13, the wall thickness stiffness diagnosis initialization unit (72) has a wall thickness calculation unit (76).

The wall thickness stiffness diagnosis initialization unit (72) sets an initial value to the wall thickness stiffness diagnosis setting value (302) as shown below. That is, the value of the density measurement coefficient Cd (201a) is substituted for the initial coefficient Cd0 (302a), the value of the density measurement coefficient fa (201b) is substituted for the initial coefficient fa0 (302b), the value of the diagnosis date and time (201x) is substituted for the initial date and time (302x), the value of the drive time (201y) is substituted for the initial drive time (302y), and the value of the integrated flow rate (201z) is substituted for the initial integrated flow rate (302z). In addition, the wall thickness stiffness diagnosis initialization unit (72) substitutes the value of the vibration pipe inner diameter d (303c) for the initial inner diameter d0 (302c). Here, the first time, there is no change in the wall thickness. In addition, the thickness stiffness diagnosis initialization unit (72) resets the initialization execution command (302u).

The wall thickness/rigidity diagnosis initialization unit (72) initializes the wall thickness/rigidity diagnosis result (301) as shown below. That is, the value of the diagnosis date and time (201x) is substituted for the diagnosis date and time (301x), the value of the drive time (201y) is substituted for the drive time (301y), the value of the integrated flow rate (201z) is substituted for the integrated flow rate (301z), and the vibration tube inner diameter d (303c) is set to the inner diameter dc (301c). The wall thickness/rigidity diagnosis initialization unit (72) also calculates the initial wall thickness by the wall thickness calculation unit (76) and sets it to the wall thickness tc (301d). The wall thickness/rigidity diagnosis initialization unit (72) also substitutes the vibration tube inner diameter d (303c) and the vibration tube outer diameter D (303a) into the above-mentioned formula (36) to obtain the wall thickness t and substitutes it for the wall thickness tc (301d). Furthermore, the thickness stiffness diagnosis initialization unit (72) sets the thickness change dt (301e) to a value of 0.0, sets the thickness change rate rt (301f) to a value of 0.0, sets the stiffness change rate aK (301g) to a value of 1.0, resets the inner diameter abnormality (301k), resets the thickness abnormality (301l), resets the thickness change abnormality (301m), resets the thickness change rate abnormality (301n), resets the stiffness change rate abnormality (301o), resets the corrosion abnormality (301p), and resets the adhesion abnormality (301q). The thickness stiffness diagnosis initialization unit (72) also sets an initialization flag (301t) to indicate that the thickness stiffness diagnosis result (301) has been initialized. The thickness stiffness diagnosis initialization unit (72) also sets an update flag (301s) to indicate that the thickness stiffness diagnosis result (301) has been updated.

The density diagnosis completion signal (210) is reset and the process waits until the next time the density error diagnosis process is executed. The thickness stiffness diagnosis initialization unit (72) also sets the thickness stiffness diagnosis completion signal (310) to indicate that the thickness stiffness diagnosis process has ended.

(3-3-5. Thickness and stiffness calculation processing)
The thickness stiffness calculation process by the thickness stiffness calculation unit (73) of the thickness stiffness diagnosis unit (70) will be described with reference to Fig. 14. Fig. 14 is a diagram showing an example of the thickness diagnosis process 3 according to the embodiment. As shown in Fig. 14, the thickness stiffness calculation unit (73) has a thickness calculation unit (77) and a stiffness calculation unit (78).

The thickness stiffness calculation unit (73) calculates the thickness change rate by the thickness calculation unit (77) as shown below. That is, the thickness calculation unit (77) calculates the thickness stiffness diagnosis result (301) using the above-mentioned formulas (42) to (45). At this time, the thickness calculation unit (77) uses the density diagnosis result (201), the thickness stiffness diagnosis set value (302), and the vibration tube design value (303) to calculate the inner diameter dc (301c), the thickness tc (301d), the thickness change dt (301e), and the thickness change rate rt (301f). Note that the thickness calculation unit (77) can also calculate only a part of the above-mentioned thickness stiffness diagnosis result (301).

The thickness and stiffness calculation unit (73) calculates the stiffness change rate by the stiffness calculation unit (78) as shown below. That is, the thickness calculation unit (77) calculates the stiffness change rate aK (301g) using the above-mentioned formula (46). At this time, the thickness and stiffness calculation unit (73) uses the density diagnosis result (201), the thickness and stiffness diagnosis setting value (302), and the vibration pipe design value (303).

The thickness/rigidity calculation unit (73) sets the diagnosis information of the thickness/rigidity diagnosis result (301) as shown below. That is, the thickness/rigidity calculation unit (73) substitutes the value of the diagnosis date/time (201x) for the diagnosis date/time (301x), the value of the drive time (201y) for the drive time (301y), and the value of the integrated flow rate (201z) for the integrated flow rate (301z).

(3-3-6. Initialization process for thickness and stiffness change)
A description will be given of a thickness stiffness change initialization process by the thickness stiffness change initialization unit (74) of the thickness stiffness diagnosis unit (70) with reference to Fig. 15. Fig. 15 is a diagram showing an example of a thickness stiffness diagnosis process 4 according to the embodiment.

The thickness stiffness change initialization unit (74) sets the initial value of the thickness stiffness diagnosis setting value (302) as shown below. That is, the thickness stiffness change initialization unit (74) assigns the value of the density measurement coefficient Cd (201a) to the initial coefficient Cd0 (302a), the value of the density measurement coefficient fa (201b) to the initial coefficient fa0 (302b), the value of the diagnosis date and time (201x) to the initial date and time (302x), the value of the drive time (201y) to the initial drive time (302y), the value of the integrated flow rate (201z) to the initial integrated flow rate (302z), and the value of the inner diameter dc (301c) to the initial inner diameter d0 (302c). The thickness stiffness change initialization unit (74) also resets the initialization execution command (302u).

The thickness stiffness change initialization unit (74) initializes the thickness stiffness diagnosis result (301) as shown below. That is, the thickness/rigidity change initialization unit (74) assigns the value of the diagnosis date and time (201x) to the diagnosis date and time (301x), assigns the value of the drive time (201y) to the drive time (301y), assigns the value of the integrated flow rate (201z) to the integrated flow rate (301z), sets the value of the thickness change dt (301e) to 0.0, sets the value of the thickness change rate rt (301f) to 1.0, sets the value of the stiffness change rate aK (301g) to 1.0, resets the inner diameter abnormality (301k), resets the thickness abnormality (301l), resets the thickness change abnormality (301m), resets the thickness change rate abnormality (301n), resets the stiffness change rate abnormality (301o), resets the corrosion abnormality (301p), and resets the adhesion abnormality (301q).

The thickness stiffness change initialization unit (74) sets the initialization flag (301t) to indicate that the thickness stiffness diagnosis result (301) has been initialized. It also sets the update flag (301s) to indicate that the thickness stiffness diagnosis result (301) has been updated. The thickness stiffness change initialization unit (74) also resets the density diagnosis completion signal (210) and waits until the density error diagnosis process is executed next time. The thickness stiffness change initialization unit (74) also sets the thickness stiffness diagnosis completion signal (310) to indicate that the thickness stiffness diagnosis process has ended.

(3-3-7. Thickness and rigidity change determination process)
The thickness stiffness change determination process by the thickness stiffness change determination unit (75) of the thickness stiffness diagnosis unit (70) will be described with reference to Fig. 16. Fig. 16 is a diagram showing an example of the thickness stiffness diagnosis process 5 according to the embodiment. As shown in Fig. 16, the thickness stiffness change determination unit (75) has an abnormality determination unit (79).

The thickness stiffness change determination unit (75), as shown below, uses the abnormality determination function (79) to compare the thickness stiffness diagnosis result (301) and density diagnosis result (201) with the thickness stiffness diagnosis set value (302), set diagnostic abnormality information in the thickness stiffness diagnosis result (301), and determine a diagnostic abnormality. That is, the thickness stiffness change determination unit (75) compares the thickness stiffness change rate of the thickness stiffness diagnosis result (301), the coefficient change rate of the density diagnosis result (201), and the allowable value of the thickness stiffness diagnosis set value (302) to determine an abnormality.

The thickness and stiffness change determination unit (75) uses the above-mentioned formula (47) to compare the inner diameter dc (301c) with the inner diameter tolerance (302k). If it is outside the tolerance, the thickness and stiffness change determination unit (75) sets the inner diameter abnormality (301k). On the other hand, if it is within the tolerance, the thickness and stiffness change determination unit (75) resets the inner diameter abnormality (301k). In the case of corrosion, the inner diameter dc (301c) becomes large.

The thickness/rigidity change determination unit (75) also uses the above-mentioned formula (48) to compare the thickness tc (301d) with the thickness tolerance (302l). If it is outside the tolerance, the thickness/rigidity change determination unit (75) sets the thickness abnormality (301l). On the other hand, if it is within the tolerance, the thickness/rigidity change determination unit (75) resets the thickness abnormality (301l). In the case of corrosion, the thickness tc (301d) becomes smaller.

The thickness/rigidity change determination unit (75) also uses the above-mentioned formula (49) to compare the thickness change dt (301e) with the thickness change tolerance (302m). If it is outside the tolerance, the thickness/rigidity change determination unit (75) sets the thickness change abnormality (301m). On the other hand, if it is within the tolerance, the thickness/rigidity change determination unit (75) resets the thickness change abnormality (301m). In the case of corrosion, the thickness change dt (301e) becomes negative.

The thickness/rigidity change determination unit (75) also uses the above-mentioned formula (50) to compare the thickness change rate rt (301f) with the thickness change rate tolerance (302n). If it is outside the tolerance, the thickness/rigidity change determination unit (75) sets the thickness change rate abnormality (301n). On the other hand, if it is within the tolerance, the thickness/rigidity change determination unit (75) resets the thickness change rate abnormality (301n). In the case of corrosion, the thickness change rate rt (301f) becomes smaller than 1.

The thickness/rigidity change determination unit (75) also uses the above-mentioned formula (51) to compare the stiffness change rate aK (301g) with the stiffness change rate tolerance (302o). If it is outside the tolerance, the thickness/rigidity change determination unit (75) sets the stiffness change rate abnormality (301o). On the other hand, if it is within the tolerance, the thickness/rigidity change determination unit (75) resets the stiffness change rate abnormality (301o). In the case of corrosion, the stiffness change rate aK (301g) becomes smaller than 1.

Furthermore, the thickness/rigidity change determination unit (75) performs a corrosion determination. At this time, if the above-mentioned formula (52) is satisfied, the thickness/rigidity change determination unit (75) sets the corrosion abnormality (301p). On the other hand, if the above-mentioned formula (52) is not satisfied, the thickness/rigidity change determination unit (75) resets the corrosion abnormality (301p).

The thickness/rigidity change determination unit (75) also performs adhesion determination. At this time, if the above-mentioned formula (53) is satisfied, the thickness/rigidity change determination unit (75) sets adhesion abnormality (301q). On the other hand, if the above-mentioned formula (53) is not satisfied, the adhesion abnormality (301q) is reset.

The thickness stiffness change determination unit (75) resets the initialization flag (301t) to indicate that the thickness stiffness diagnosis result (301) has not been initialized. The thickness stiffness change determination unit (75) also sets the update flag (301s) to indicate that the thickness stiffness diagnosis result (301) has been updated.

The thickness stiffness change determination unit (75) resets the density diagnosis completion signal (210) and waits until the density error diagnosis process is executed next time. The thickness stiffness change determination unit (75) also sets the thickness stiffness diagnosis completion signal (310) to indicate that the thickness stiffness diagnosis process has ended.

(3-3-8. Thickness and stiffness diagnosis process using density calibration result (151))
As described above, the thickness/rigidity diagnosis unit (70) generates the thickness/rigidity diagnosis result (301) using the density diagnosis result (201) generated by the density error diagnosis unit (61). On the other hand, the thickness/rigidity diagnosis unit (70) can also generate the thickness/rigidity diagnosis result using the density calibration result (151). In the following, the thickness/rigidity diagnosis process that does not involve the density error diagnosis process will be described.

The thickness/rigidity diagnosis unit (70) acquires the density measurement coefficient Cdc (151a), which is the density calibration result (151), instead of the density measurement coefficient Cd (201a), which is the density diagnosis result (201). Also, the thickness/rigidity diagnosis unit (70) acquires the density measurement coefficient fac (151b), which is the density calibration result (151), instead of the density measurement coefficient fa (201b), which is the density diagnosis result (201).

The thickness stiffness diagnosis unit (70) calculates the coefficient change rate aCd using the initial coefficient Cd0 (302a) and the density measurement coefficient Cdc (151a), which is the density calibration result (151), instead of the coefficient change rate aCd (201e), which is the density diagnosis result (201) calculated as the ratio of the initial coefficient Cd0 (202a) and the density measurement coefficient Cdc (151a) to the initial value.

The thickness stiffness diagnosis unit (70) calculates the coefficient change rate afa using the initial coefficient fa0 (302b) and the density measurement coefficient fac (151b), which is the density calibration result (151), instead of the coefficient change rate afa (201f), which is the density diagnosis result (201) calculated as the ratio of the initial coefficient Cd0 (202a) and the density measurement coefficient Cdc (151a) to the initial value.

The thickness/rigidity diagnosis unit (70) acquires the calibration date/time (151x), which is the density calibration result (151), instead of the diagnosis date/time (201x), which is the density diagnosis result (201). The thickness/rigidity diagnosis unit (70) also acquires the drive time (151y), which is the density calibration result (151), instead of the drive time (201y), which is the density diagnosis result (201). The thickness/rigidity diagnosis unit (70) also acquires the integrated flow rate (151z), which is the density calibration result (151), instead of the integrated flow rate (201z), which is the density diagnosis result (201).

The thickness stiffness diagnosis unit (70) generates a density calibration completion signal 2 (161) in parallel with the density calibration completion signal (160) instead of the density diagnosis completion signal (210).

(3-4. Flow Error Diagnosis and Simple Correction Processing)
17 to 21 and equations, the flow error diagnosis and simple correction process executed by the flow error diagnosis simple correction unit (80) of the diagnosis device (2) according to the embodiment will be described. Below, the theoretical formula of the flow error diagnosis and simple correction process will be explained, and then the overall flow error diagnosis and simple correction process, the initialization determination process, the flow initialization process, the rigidity thickness initialization process, and the flow correction coefficient update process will be described in that order.

(3-4-1. Theoretical formula for flow rate error diagnosis and simple correction processing)
The theoretical formula for the flow rate error diagnosis and simple correction process will be described below. First, the flow rate correction coefficient fk(28u) included in the following formula (54) is found from the density calibration result, and the mass flow rate is simply corrected.

In the above equation (54), the flow measurement coefficient Cq represents the flow measurement coefficient Cq (28f), the phase difference θ0 represents the phase difference θ (28d), the frequency f represents the frequency f (28c), the mass flow rate Qmc represents the mass flow rate Qm (28a) after simple correction, and the value of the correction coefficient fk represents the flow correction coefficient fk (28u).

The flow rate measurement coefficient Cq in the mass flow rate measurement formula shown in the above formula (2) includes the stiffness (spring constant) ks of the torsional vibration of the vibrating tube and the ratio of the resonance frequencies of the bending vibration and torsional vibration. The stiffness change rate measured by the diagnostic device (2) is the stiffness in the vibration direction, but is thought to fluctuate similarly to the stiffness of the torsional vibration. The change in wall thickness is related to the change in the resonance frequency. By calculating the correction coefficient fk from the rate of change obtained by the diagnostic device (2), simple correction of the mass flow rate is possible.

In the diagnostic process described above, the rigidity and thickness are determined from the density measurement coefficient Cd and density measurement coefficient fa. Here, the density measurement coefficient Cd and density measurement coefficient fa contain information about the vibrating tube. Therefore, by using the density measurement coefficient itself or the rate of change of the density measurement coefficient, simple correction of the mass flow rate is possible.

The calculation formula for the flow rate correction coefficient fkq using the stiffness change rate aK (301g), the wall thickness change rate rt (301f), the coefficient change rate of the density measurement coefficient aCd (201e), and the coefficient change rate of the density measurement coefficient afa (201f) is shown in the following formula (55). Here, a simple correction is performed by substituting the flow rate correction coefficient fkq for the flow rate correction coefficient fk (28u).

In the above formula (55), the coefficient Ckx indicates the flow correction coefficient Ckx (28v) and is a value that depends on the characteristics of the detection unit (10) of the Coriolis mass flowmeter (1). The correction formula for the flow correction coefficient fkq may be an approximate straight line or an approximate curve. It is not necessary to use all the change rates. The parameters and correction coefficients to be used are determined using multiple regression analysis, inference using AI (Artificial Intelligence), etc. The flow correction coefficient Ckx (28v) depends on the detector, so it is set in advance for each detector. There are methods such as actually corroding the vibrating tube and calculating the effects of corrosion through simulation.

In the above formula (55), the wall thickness change rate rt (301f) is used, but the correction formula for the flow rate correction coefficient fkq can also be constructed using the inner diameter dc (301c), the wall thickness tc (301d), or the wall thickness change dt (301e).

Note that traditional flow rate calibration requires actual flow of water or other fluids, which requires separate equipment. Density calibration can be performed by measuring two fluids with known densities, namely air and water, and does not require special equipment. Unlike flow rate calibration, which involves flowing a fluid, there is a high possibility of error.

When mass flow calibration is performed, the error that was corrected using the flow correction coefficient fk (28u) is absorbed by the flow measurement coefficient Cq (28f). Therefore, after mass flow calibration, it is necessary to set the flow correction coefficient fk (28u) to its initial value of 1.0. In equation (55), the flow correction coefficient Ckx (28v) is fixed because it depends on the characteristics of the detection unit (10). Therefore, the rate of change must be initialized at the start or when mass flow calibration is performed.

Each rate of change is calculated within the thickness and stiffness diagnosis section (70). It is also possible to issue an initialization command to the thickness and stiffness diagnosis function (70) to perform initialization, but the initial values are stored within the flow error diagnosis simple correction function (80), and the following formula (56) is shown, using the rate of change from the initial values.

At this time, the initial stiffness change rate aK0 (502g), initial thickness change rate rt0 (502f), initial coefficient change rate aCd0 (502a), and initial coefficient change rate afa0 (502b) are used as initial values.

When calibrating mass flow rate, the flow rate correction coefficient fk (28u) is set to an initial value of 1.0. Mass flow rate calibration and density calibration are not necessarily synchronized. In particular, if the stiffness has changed since the previous density calibration, a flow rate error will occur. Therefore, to reduce errors in the simple correction of the flow rate measurement coefficient, density calibration must be performed at the same time as mass flow rate calibration.

Changing the flow rate measurement coefficient creates discontinuities in the flow rate measurement results. If the flow rate fluctuations are within an acceptable range, there is also the option of prioritizing the continuity of the measurement values. If the flow rate correction coefficient before simple correction is fk and the flow rate correction coefficient after simple correction is fkq, the flow rate fluctuation rate rqd (501c) is defined as the following equation (57). The mass flow rate before simple correction is mass flow rate Qmc, and the mass flow rate after simple correction is mass flow rate Qmcq.

The flow rate fluctuation tolerance (502h) is set to rqdlim and is compared with the flow rate change rate rqd. By determining whether or not the flow rate correction coefficient fk can be replaced, small fluctuations can be suppressed. In this case, the conditional formula is the following formula (58).

If the flow rate fluctuation tolerance ratio value rqdlim is set to 0, it is always replaced. If the flow rate correction coefficient fk is not updated, the flow rate correction coefficient fk will maintain the value from the last time it was updated.

The flow rate error rate rqe (501b) of the mass flow measurement from the time of flow rate calibration is calculated using the flow rate correction coefficient fkq after simple correction, as shown in the following formula (59). The flow rate error rate rqe (501b) is used as a basis for diagnosing the flow rate error. The mass flow rate at the time of flow rate calibration is defined as the mass flow rate Qm.

The flow rate error rate rqe (501b) is compared with the flow rate error alarm value rqelim, and if the fluctuation becomes large, a flow rate diagnosis abnormality (501r) is set. The flow rate error alarm value rqelim indicates the flow rate error alarm value (502r). In this case, the condition formula is the following formula (60).

By setting the flow rate diagnosis abnormality (501r), the user can be notified of an abnormality in the device. In addition, the flow rate error rate rqe can be displayed on the display operation unit (30) or external device (31), and it is also possible to input whether or not the coefficient should be updated.

The flow rate error diagnosis and simple correction process described above includes a diagnosis process that monitors the flow rate error and issues an alarm, and a simple correction process that updates the flow rate correction coefficient fkq to reduce the density error, and it is possible to use only one of them.

(3-4-2. Overall Processing of Flow Error Diagnosis and Simple Correction Processing)
The overall flow rate error diagnosis and simple correction process will be described with reference to Fig. 17. Fig. 17 is a diagram showing an example of the overall flow rate error diagnosis and simple correction process according to the embodiment. The configuration of the flow rate error diagnosis simple correction unit (80) of the diagnosis device (2) will be described below.

As shown in FIG. 17, the flow error diagnosis simple correction unit (80) is part of the diagnosis control unit (60). The flow error diagnosis simple correction unit (80) also has an initialization determination unit (81), a flow initialization unit (82), a rigidity thickness initialization unit (83), and a flow correction coefficient update unit (84), which respectively execute an initialization determination process, a flow initialization process, a rigidity thickness initialization process, and a flow correction coefficient update process.

The flow error diagnosis simple correction unit (80) executes processing when the thickness stiffness diagnosis completion signal (310) or the flow calibration completion signal (120) is set. The flow error diagnosis simple correction unit (80) also updates the flow diagnosis result (501) and updates the parameters (28) based on the thickness stiffness diagnosis result (301) and the density diagnosis result (201).

The initialization determination unit (81) sets the initialization execution signal 1 (507), the initialization execution signal 2 (508), or the update execution signal (509). The initialization determination unit (81) makes a determination based on the flow calibration completion signal (120), the thickness stiffness diagnosis result (301), the thickness stiffness diagnosis completion signal (310), and the flow diagnosis setting value (502).

The flow rate initialization unit (82) sets the parameters (28), the flow rate diagnosis result (501), and the flow rate diagnosis set value (502) from the parameters (28), the density diagnosis result (201), and the wall thickness stiffness diagnosis result (301), and resets the flow rate calibration completion signal (120). The flow rate initialization unit (82) executes the initialization process when the mass flow rate calibration process is executed. The flow rate initialization unit (82) also executes the process when the initialization execution signal 1 (507) is set.

The rigidity/thickness initialization unit (83) sets the parameters (28), flow rate diagnosis result (501) and flow rate diagnosis set value (502) from the density diagnosis result (201) and thickness/rigidity diagnosis result (301), and resets the thickness/rigidity diagnosis completion signal (310). The rigidity/thickness initialization unit (83) executes initialization processing when the thickness/rigidity diagnosis unit (70) is executed. The rigidity/thickness initialization unit (83) also executes processing when the initialization execution signal 2 (508) is set.

The flow correction coefficient update unit (84) sets the parameters (28) and the flow diagnosis result (501) from the parameters (28), the density diagnosis result (201), the thickness stiffness diagnosis result (301), and the flow diagnosis set value (502), and resets the thickness stiffness diagnosis completion signal (310). In addition, the flow correction coefficient update unit (84) executes processing when the update execution signal (509) is set.

(3-4-3. Initialization Determination Process)
The initialization judgment process will be described with reference to FIG. 18. The initialization judgment process by the initialization judgment unit (81) of the flow error diagnosis simple correction unit (80) will be described. FIG. 18 is a diagram showing an example of the flow error diagnosis and simple correction process 1 according to the embodiment. As shown in FIG. 18, the initialization judgment unit (81) executes the process when the flow calibration completion signal (120) or the thickness stiffness diagnosis completion signal (310) is set. In addition, the initialization judgment unit (81) outputs an initialization execution signal 1 (507), an initialization execution signal 2 (508), and an update execution signal (509) as the thickness stiffness diagnosis result (301) based on the initialization flag (301t) and the initial date and time (502x) and the initialization execution command (502u) as the flow diagnosis set value (502). The flow of the initialization judgment process will be described later in [5. Flow of each process of the calibration device (3) and the diagnosis device (2)].

(3-4-4. Flow rate initialization process)
The density flow rate initialization process by the flow rate initialization unit (82) of the flow rate error diagnosis simple correction unit (80) will be described with reference to Fig. 19. Fig. 19 is a diagram showing an example of flow rate error diagnosis and simple correction process 3 according to the embodiment. As shown in Fig. 19, the flow rate initialization unit (82) has a rigidity thickness selection unit (85).

The flow rate initialization unit (82) initializes the flow rate diagnosis setting value (502) by the stiffness/thickness selection unit (85) as shown below. That is, the flow rate initialization unit (82) selects the initial value of the change rate. At this time, if the diagnosis date and time (301x) is not set, the flow rate initialization unit (82) sets the initial coefficient change rate aCd0 (502a), the initial coefficient change rate afa0 (502b), the initial thickness change rate rt0 (502f), and the initial stiffness change rate aK0 (502g) to the value 1.0. On the other hand, when the diagnosis date and time (301x) is set, the flow rate initialization unit (82) assigns the value of the coefficient change rate aCd (201e) to the initial coefficient change rate aCd0 (502a), assigns the value of the coefficient change rate afa (201f) to the initial coefficient change rate afa0 (502b), assigns the value of the thickness change rate rt (301f) to the initial thickness change rate rt0 (502f), assigns the value of the stiffness change rate aK (301g) to the initial stiffness change rate aK0 (502g), assigns the value of the flow rate calibration date and time (28h) to the initial date and time (502x), assigns the value of the flow rate calibration drive time (28i) to the initial drive time (502y), and assigns the value of the flow rate calibration integrated flow rate (28j) to the initial integrated flow rate (502z). The flow rate initialization unit (82) also sets an initialization execution command (502u) and performs initialization the next time density calibration is performed. Furthermore, the flow rate initialization unit (82) sets the flow rate correction coefficient fk (28u) to an initial value of 1.0.

The flow rate initialization unit (82) initializes the flow rate diagnosis result (501) as shown below. That is, the flow rate initialization unit (82) assigns a value of 1.0 to the flow rate correction coefficient fkq (501a), assigns a value of 0.0 to the flow rate error rate rqe (501b), assigns a value of 0.0 to the flow rate fluctuation rate rqd (501c), assigns the value of the flow rate calibration date and time (28h) to the correction date and time (501x), assigns the value of the flow rate calibration drive time (28i) to the drive time (501y), and assigns the value of the flow rate calibration integrated flow rate (28j) to the integrated flow rate (501z). The flow rate initialization unit (82) also resets the flow rate diagnosis abnormality (501r). The flow rate initialization unit (82) also sets the initialization flag (501t) to indicate that the flow rate diagnosis result (501) has been initialized. The flow rate initialization unit (82) also sets the update flag (501s) to indicate that the flow rate diagnosis result (501) has been updated. Furthermore, the flow rate initialization unit (82) resets the flow rate calibration completion signal (120) and waits for the next flow rate calibration process to be performed.

(3-4-5. Rigidity and thickness initialization process)
The rigidity thickness initialization process by the rigidity thickness initialization unit 83 of the flow rate error diagnosis simple correction unit 80 will be described with reference to Fig. 20. Fig. 20 is a diagram showing an example of flow rate error diagnosis and simple correction process 3 according to the embodiment.

The stiffness thickness initialization unit (83) initializes the flow rate diagnosis setting value (502) as shown below. That is, the stiffness thickness initialization unit (83) assigns the value of the coefficient change rate aCd (201e) to the initial coefficient change rate aCd0 (502a), assigns the value of the coefficient change rate afa (201f) to the initial coefficient change rate afa0 (502b), assigns the value of the thickness change rate rt (301f) to the initial thickness change rate rt0 (502f), assigns the value of the stiffness change rate aK (301g) to the initial stiffness change rate aK0 (502g), assigns the value of the diagnosis date and time (301x) to the initial date and time (502x), assigns the value of the drive time (301y) to the initial drive time (502y), and assigns the value of the integrated flow rate (301z) to the initial integrated flow rate (502z). In addition, the rigidity thickness initialization unit (83) resets the initialization execution command (502u) and waits for an initialization command from the outside. Furthermore, the rigidity thickness initialization unit (83) sets the flow rate correction coefficient fk (28u) to an initial value of 1.0.

The rigid thickness initialization unit (83) initializes the flow diagnosis result (501) as shown below. That is, the rigid thickness initialization unit (83) assigns a value of 1.0 to the flow correction coefficient fkq (501a), assigns a value of 0.0 to the flow error rate rqe (501b), assigns a value of 0.0 to the flow rate fluctuation rate rqd (501c), assigns the value of the diagnosis date and time (301x) to the correction date and time (501x), assigns the value of the drive time (301y) to the drive time (501y), and assigns the value of the integrated flow rate (301z) to the integrated flow rate (501z). The rigid thickness initialization unit (83) also resets the flow diagnosis abnormality (501r). The rigid thickness initialization unit (83) also sets the initialization flag (501t) to indicate that the flow diagnosis result (501) has been initialized. In addition, the stiffness/thickness initialization unit (83) sets the update flag (501s) to indicate that the flow rate diagnosis result (501) has been updated. Furthermore, it resets the stiffness/thickness diagnosis completion signal (310) and waits for the next execution of the stiffness/thickness diagnosis process.

(3-4-6. Flow rate correction coefficient update process)
The flow rate correction coefficient update process by the flow rate correction coefficient update unit (84) of the flow rate error diagnosis simple correction unit (80) will be described with reference to Fig. 21. Fig. 21 is a diagram showing an example of flow rate error diagnosis and simple correction process 4 according to the embodiment. As shown in Fig. 21, it has a flow rate correction coefficient calculation unit (86), a flow rate fluctuation comparator 1 (87), a flow rate correction coefficient setter (88), and a flow rate fluctuation comparator 2 (89).

The flow correction coefficient update unit (84) uses the flow correction coefficient calculation unit (86) to calculate the flow correction coefficient, the flow error rate, and the flow rate fluctuation rate. That is, the flow correction coefficient update unit (84) calculates the flow correction coefficient fkq from the above-mentioned equation (56) and substitutes it into the flow correction coefficient fkq (501a). The flow correction coefficient update unit (84) also calculates the flow rate fluctuation rate rqd from the above-mentioned equation (57) and substitutes it into the flow rate fluctuation rate rqd (501c). The flow correction coefficient update unit (84) also calculates the flow error rate rqe from the above-mentioned equation (59) and substitutes it into the flow rate error rate rqe (501b).

The flow correction coefficient update unit (84) sets the flow diagnosis result (501) as shown below. That is, the flow correction coefficient update unit (84) assigns the value of the diagnosis date and time (301x) to the correction date and time (501x), assigns the value of the drive time (301y) to the drive time (501y), and assigns the value of the integrated flow rate (301z) to the integrated flow rate (501z).

The flow correction coefficient update unit (84) uses the flow fluctuation comparator 1 (87) to compare the absolute value of the flow rate fluctuation rate rqd (501c) with the flow rate fluctuation tolerance value (502h). At this time, the flow correction coefficient update unit (84) makes a judgment using the above-mentioned formula (58). If the absolute value of the flow rate fluctuation rate rqd (501c) is greater than the flow rate fluctuation tolerance value (502h), the flow correction coefficient update unit (84) sets the flow coefficient selection signal (504) and sets the value of the flow correction coefficient fkq (501a) to the flow correction coefficient fk (28u) using the flow correction coefficient setter (88).

The flow correction coefficient update unit (84) executes the following process using the flow fluctuation comparator 2 (89). That is, the flow correction coefficient update unit (84) uses the above-mentioned formula (60) to compare the flow error rate rqe (501b) with the flow error alarm value (502r). At this time, if the absolute value of the flow error rate rqe (501b) is greater than the flow error alarm value (502r), the flow correction coefficient update unit (84) sets a flow diagnosis abnormality (501r). On the other hand, if the absolute value of the flow error rate rqe (501b) is equal to or less than the flow error alarm value (502r), the flow correction coefficient update unit (84) resets the flow diagnosis abnormality (501r). In addition, the flow correction coefficient update unit (84) resets the initialization flag (501t), indicating that the flow diagnosis result (501) has not been initialized. In addition, the stiffness/thickness initialization unit (83) sets the update flag (501s) to indicate that the flow rate diagnosis result (501) has been updated. Furthermore, the flow rate correction coefficient update unit (84) resets the stiffness/thickness diagnosis completion signal (310) and waits for the next execution of the stiffness/thickness diagnosis process.

(3-5. Timing Prediction Diagnosis Processing)
22 to 26 and equations, the timing prediction diagnostic process executed by the timing prediction diagnostic unit (90) of the diagnostic device (2) according to the embodiment will be described. Below, after explaining the theoretical equation of the timing prediction diagnostic process, the entire timing prediction diagnostic process, the timing prediction diagnostic process using the calibration diagnostic result, the timing prediction diagnostic process using the density diagnostic result, the timing prediction diagnostic process using the wall thickness/rigidity diagnostic result, and the timing prediction diagnostic process using the flow rate diagnostic result will be described in this order.

(3-5-1. Theoretical formula for timing prediction diagnostic processing)
The theoretical formula for the timing prediction diagnosis process will be described below. Here, an example of the wall thickness change dt (301e) is shown as an example of the formula used in the timing prediction diagnosis. Similar formulas can also be created for other diagnosis values. Here, the coefficient change rate aCd (201e), the coefficient change rate afa (201f), the inner diameter dc (301c), the wall thickness tc (301d), the wall thickness change rate rt (301f), the stiffness change rate aK (301g), the density error Δρ0 (201d), the flow rate correction coefficient fkq (501a), and the flow rate error rate rqe (501b) are defined as follows.

Here, the changes are approximated using an approximate straight line or curve from multiple data points, and timing prediction diagnosis is performed. The parameters and correction coefficients used are determined using multiple regression analysis, AI inference, etc. Using the maximum rate of change from multiple data points makes it possible to make predictions under conditions where the change is greatest.

Here, we will show an example of creating an approximation line from the diagnostic results of two points and performing timing prediction diagnosis. If we create an approximation line by letting the coefficient x be the history information number, x=1 being the start, x=2 being the present, the date and time being Tmx, the drive time being Tdx, the integrated flow rate being Qmx, and the change in thickness being dtx, we obtain the following equations (61) to (63).

In the above formula (61), the coefficient am indicates the change in thickness per date and time. Furthermore, the coefficient bm indicates the change in thickness when x = 0. In the above formula (62), the coefficient ad indicates the change in thickness per drive time. Furthermore, the coefficient bd indicates the change in thickness when x = 0. In the above formula (63), the coefficient aq indicates the change in thickness per integrated flow rate. Furthermore, the coefficient bq indicates the change in thickness when x = 0. Here, the above formulas (61) to (63) give the following formulas (64) to (69).

Here, the diagnostic target value dts for the thickness change is set. The predicted value that reaches the diagnostic target value dts is obtained. If the predicted value is expressed by the date and time Tme, the drive time Tde, and the mass flow rate Qme, it becomes the following equations (70) to (72).

The flow rate correction coefficient fk (28u) indicates the flow rate error that has occurred. By entering the flow rate correction coefficient fk (28u) into the flow rate measurement formula, the flow rate error can be corrected, but since the flow rate correction coefficient fk (28u) is an estimate, it contains a certain amount of error. By using the flow rate correction coefficient fk (28u) to perform timing prediction diagnosis, it is possible to predict the date and time when the error limit value will be reached, the operating time, and the mass flow rate.

(3-5-2. Overall Processing of Timing Prediction Diagnosis Processing)
The entire timing prediction diagnosis process will be described with reference to Fig. 22. Fig. 22 is a diagram showing an example of the entire timing prediction diagnosis process according to the embodiment. The configuration of the timing prediction diagnosis unit (90) of the diagnosis device (2) will be described below.

The timing prediction diagnosis unit (90) has a history unit (91), a change trend calculation unit (92), and a prediction unit (93), and predicts timing from the results of any of the density calibration unit (51), density error diagnosis unit (61), thickness stiffness diagnosis unit (70), and flow rate error diagnosis simple correction unit (80).

First, the timing prediction diagnosis unit (90) determines whether an update flag is set. Here, the timing prediction diagnosis unit (90) checks the update flag of the diagnosis data included in the result of each diagnosis. That is, the timing prediction diagnosis unit (90) checks the update flag (151s) included in the density calibration result (151) which is the calibration result of the density calibration unit (51), checks the update flag (301s) included in the thickness stiffness diagnosis result (301) which is the diagnosis result of the thickness stiffness diagnosis unit (70), checks the update flag (201s) included in the density diagnosis result (201) which is the diagnosis result of the density error diagnosis unit (61), and checks the update flag (501s) included in the flow diagnosis result (501) which is the correction result of the flow error diagnosis simple correction unit (80). If none of the above update flags are set, the timing prediction diagnosis unit (90) ends the process.

Next, the timing prediction diagnosis unit (90) stores the above diagnosis results using the history unit (91). Next, the timing prediction diagnosis unit (90) calculates a change trend value (601) from the updated data in the history unit (91) using the change trend calculation unit (92). At this time, the timing prediction diagnosis unit (90) approximates the change with the approximation line or approximation curve shown in the above-mentioned equations (64) to (69). The timing prediction diagnosis unit (90) determines the parameters and correction coefficients to be used using multiple regression analysis, AI inference, etc.

Then, the timing prediction diagnosis unit (90) calculates a predicted value from the change trend value (601) and the diagnosis target value (602) using the prediction unit (93), and outputs the result of the timing prediction diagnosis (603). At this time, the timing prediction diagnosis unit (90) performs the calculations shown in the above-mentioned equations (70) to (72). The timing prediction diagnosis unit (90) transmits the calculated timing prediction diagnosis result (603) to the display operation unit (30) of the Coriolis mass flowmeter (1) or the external device (31). Finally, the timing prediction diagnosis unit (90) resets the update flag.

(3-5-3. Timing prediction diagnosis process using density calibration results)
A timing prediction diagnostic process using the density calibration result will be described with reference to Fig. 23. Fig. 23 is a diagram showing an example of timing prediction diagnostic process 1 according to the embodiment.

The timing prediction diagnosis unit (90) performs timing prediction diagnosis from the density calibration result (151) of the density calibration unit (51) as shown below. That is, the timing prediction diagnosis unit (90) executes timing prediction diagnosis processing when the update flag (151s) included in the density calibration result (151) is set. At this time, the history unit (91) of the timing prediction diagnosis unit (90) imports data using the setting of the update flag (151s) as a trigger. The history unit (91) can also select necessary data from the input data. Here, the density measurement coefficient Cdc (151a) and the density measurement coefficient fac (151b) are important parameters for timing prediction. The history unit (91) resets the update flag (151s) when the import is completed.

(3-5-4. Timing Prediction Diagnosis Processing Using Density Diagnosis Results)
A timing prediction diagnostic process using the density diagnosis result will be described with reference to Fig. 24. Fig. 24 is a diagram showing an example of timing prediction diagnostic process 2 according to the embodiment.

The timing prediction diagnosis unit (90) performs timing prediction diagnosis from the density diagnosis result (201) of the density error diagnosis unit (61) as shown below. That is, the timing prediction diagnosis unit (90) executes timing prediction diagnosis processing when the update flag (201s) included in the density diagnosis result (201) is set. At this time, the history unit (91) of the timing prediction diagnosis unit (90) imports data, triggered by the setting of the update flag (201s). The history unit (91) can also select necessary data from the input data. Here, the density error Δρ0 (201d), the coefficient change rate aCd (201e), and the coefficient change rate afa (201f) are important parameters for timing prediction. The history unit (91) resets the update flag (201s) when the import is completed.

(3-5-5. Timing Prediction Diagnosis Processing Using Thickness and Stiffness Diagnosis Results)
The timing prediction diagnostic process using the thickness stiffness diagnosis result will be described with reference to Fig. 25. Fig. 25 is a diagram showing an example of timing prediction diagnostic process 3 according to the embodiment.

The timing prediction diagnosis unit (90) performs timing prediction diagnosis from the thickness stiffness diagnosis result (301) of the thickness stiffness diagnosis unit (70) as shown below. That is, the timing prediction diagnosis unit (90) executes timing prediction diagnosis processing when the update flag (301s) included in the thickness stiffness diagnosis result (301) is set. At this time, the history unit (91) of the timing prediction diagnosis unit (90) imports data triggered by the setting of the update flag (301s). The history unit (91) can also select necessary data from the input data. Here, the inner diameter dc (301c), the thickness tc (301d), the thickness change rate rt (301f), and the stiffness change rate aK (301g) are important parameters for timing prediction. The history unit (91) resets the update flag (301s) when the import is completed.

(3-5-6. Timing Prediction Diagnosis Processing Using Flow Rate Diagnosis Results)
A timing prediction diagnostic process using the flow rate diagnosis result will be described with reference to Fig. 26. Fig. 26 is a diagram showing an example of timing prediction diagnostic process 4 according to the embodiment.

The timing prediction diagnosis unit (90) performs timing prediction diagnosis from the flow diagnosis result (501) of the flow error diagnosis simple correction unit (80) as shown below. That is, the timing prediction diagnosis unit (90) executes timing prediction diagnosis processing when the update flag (501s) included in the flow diagnosis result (501) is set. The history unit (91) of the timing prediction diagnosis unit (90) imports data when the update flag (501s) is set. The history unit (91) can also select necessary data from the input data. Here, the flow correction coefficient fkq (501a) and the flow error rate rqe (501b) are important parameters for timing prediction. The history unit (91) resets the update flag (501s) when the import is completed.

4. Processing results of each process of the diagnostic device (2)
27 to 37, the results of each process of the diagnosis device (2) according to the embodiment and their effects will be described. The following describes the density diagnosis result, wall thickness rigidity diagnosis result, flow rate diagnosis result, and timing prediction diagnosis result in that order.

(4-1. Density diagnosis results and effects)
The density diagnosis result and the effect will be described with reference to Fig. 27. Fig. 27 is a diagram showing an example of the density diagnosis result according to the embodiment. In the following, the density diagnosis result will be described, and then the effect of the density diagnosis process will be described.

(4-1-1. Density diagnosis results)
The density diagnosis result will be described with reference to Fig. 27. The density diagnosis result shows the result of flowing a corrosive fluid through a Coriolis mass flowmeter (1), performing density calibration before and after corrosion, and measuring the stiffness change together with the density calibration using the method described in Patent Document 1.

Figure 27 (1) shows the measurement data. Test # is the number of tests, with 0 indicating before corrosion. Density calibration was performed before corrosion and after the corrosive fluid was allowed to flow for a certain period of time. The Test # value indicates the number of corrosion events. As the Test # value increases, the amount of corrosion increases. Density calibration was performed with air and water. No pressure was applied. The values f1s and f2s indicate the frequency f (28c) obtained in the measurement. The values T1s and T2s indicate the temperature T (28e) at the time of measurement. The value f1 indicates the corrected frequency f1 (154) obtained by correcting the frequency f1s by the temperature T1s. The value f2 indicates the corrected frequency f2 (155) obtained by correcting the frequency f2s by the temperature T2s. Density ρ1 (158) and density ρ2 (159) indicate the density of air at standard conditions and the density of water at standard conditions, determined using temperatures T1s and T2s.

Figure 27 (2) shows the density calibration result (151) and the density diagnosis result (201). The density measurement coefficient Cdc (151a) and the density measurement coefficient fac (151b) were calculated by substituting the measured values in Figure 27 (1) into the above-mentioned formulas (21) to (24). The density fluctuation Δρ (201c) was calculated from the above-mentioned formula (27). The density of air and water was used as the measurement target density ρt (202c). Also, the density fluctuation that occurred after the previous density calibration is shown. The density error Δρ0 (201d) was calculated from the above-mentioned formula (29). The density of air and water was used as the measurement target density ρt (202c). Also, the density error from the initial state is shown. The density fluctuation Δρ (201c) is compared with the density fluctuation tolerance value (202d) by the above-mentioned formula (28), and the fluctuation is evaluated, and the replacement of the density measurement coefficient can be determined. In addition, the density error Δρ0 (201d) can be compared with the density error warning value (202h) using the above-mentioned formula (30) to set the density error abnormality (201h).

Figure 27 (3) shows the change in density measurement coefficient fac (151b) and density measurement coefficient Cdc (151a) depending on the number of corrosions. Both decrease as the amount of corrosion increases.

Figure 27 (4) shows the change in density error Δρ0 (201d) depending on the number of corrosions. The density of air and water was used as the measurement object density ρt (202c). The density variation Δρ (201c) increases as the amount of corrosion increases. The density error Δρ0 (201d) changes depending on the setting of the measurement object density ρt (202c). Since the corrosive fluid is flowed and corrosion is forced, the density error Δρ0 (201d) changes significantly. In this way, by density calibration, the density error Δρ0 (201d) can be estimated as the density diagnosis result (201) according to the embodiment, and by monitoring the density error, the accuracy of the density measurement can be maintained.

(4-1-2. Effects)
As described above, the density error occurring can be estimated from the change in the density measurement coefficient obtained by density calibration. Since the density error depends on the density of the object to be measured, the density error is calculated taking into account the density of the object to be measured. A density error tolerance can be set and an alarm can be issued to notify of an abnormality. The occurrence of a density error indicates that an error has also occurred in the mass flow measurement results. It is also possible to notify that the measurement instrument needs to be readjusted. Density calibration is an important function that determines the accuracy of a Coriolis mass flowmeter and is performed in a stable situation. Therefore, accurate measurements can be made without being affected by disturbances. Changing the density measurement coefficient by density calibration creates discontinuities in the density measurement results. If the density fluctuation is within the tolerance range, there is also the option of prioritizing the continuity of the measurement values. By setting a density fluctuation tolerance, it is possible to determine whether or not the density measurement coefficient can be replaced, and the fluctuation of the density measurement results can be suppressed. Coriolis mass flowmeters are characterized by their ability to perform accurate measurements. Density measurement is one of the basic functions of a Coriolis mass flowmeter, and the target accuracy can be maintained by monitoring the density error.

(4-2. Thickness and rigidity diagnosis results and effects)
The wall thickness stiffness diagnosis results and effects will be described with reference to Figures 28 to 32. Below, wall thickness stiffness diagnosis result 1, wall thickness stiffness diagnosis result 2, and wall thickness stiffness diagnosis result 3 will be described, and then the effects of the wall thickness stiffness diagnosis process will be described.

(4-2-1. Thickness and rigidity diagnosis result 1)
A wall thickness/rigidity diagnosis result 1 will be described with reference to Fig. 28. Fig. 28 is a diagram showing an example of a wall thickness/rigidity diagnosis result 1 according to the embodiment.

Figure 28 (1) shows the results of calculations using the formula according to the embodiment. Here, thickness and stiffness diagnosis was performed using the density calibration results shown in Figures 27 (1) and 27 (2). "Density Calibration" is the result of calculation using the formula according to the embodiment. The amount of change was calculated based on the value of Test #0. The inner diameter dc (301c), thickness tc (301d), thickness change dt (301e), thickness change rate rt (301f), and stiffness change rate aK (301g) were calculated using the above formulas (42) to (46). The changes from the initial Test #0 are also shown. The variable aKc indicates the stiffness change rate aKc measured using the method of Patent Document 1. The value was almost the same as the stiffness change rate aK (301g).

Figure 28 (2) shows the number of corrosions, thickness change dt (301e), thickness change rate rt (301f), stiffness change rate aK (301g), and stiffness change rate aKc measured using the method of Patent Document 1. The stiffness change rate aK (301g) according to the embodiment and the stiffness change rate aKc according to Patent Document 1 are the same. The thickness change rate also decreased in the same manner. In this way, the thickness change rate and stiffness change rate can be estimated as the thickness stiffness diagnosis result (301) according to the embodiment based on the density calibration result.

(4-2-2. Thickness and rigidity diagnosis result 2)
The wall thickness rigidity diagnosis result 2 will be described with reference to Fig. 29 and Fig. 30. Fig. 29 is a diagram for explaining the wall thickness rigidity diagnosis result 2 according to the embodiment. Fig. 30 is a diagram showing an example of the wall thickness rigidity diagnosis result 2 according to the embodiment.

Below, as shown in FIG. 29, a test was conducted to verify the effect of the sensitivity of the upstream sensor (13). As shown in FIG. 29, the upstream signal S1 (13a) was attenuated between the detection unit (10) and the conversion unit (20) by an attenuator (13b). This simulated a decrease in the sensitivity of the upstream sensor (13).

Figure 30 (1) shows the results of density calibration performed by changing the gain of the attenuator (13b). The variation in the density measurement coefficient Cdc (151a) and the density measurement coefficient fac (151b) was less than 0.01%. The density measurement coefficient Cdc (151a) and the density measurement coefficient fac (151b) can be obtained regardless of the gain of the attenuator (13b).

Figure 30 (2) shows the stiffness change rate aK (301g) obtained by density calibration while changing the gain of the damper (13b) and the stiffness change rate aKc obtained by the method of Patent Document 1. The stiffness change rate aK (301g) does not depend on the gain of the damper (13b). The stiffness change rate aKc depends on the gain of the damper (13b). The method of Patent Document 1 interprets that when the sensitivity of the upstream sensor (13) decreases and the upstream signal S1 (13a) becomes small, the vibration tube (11) has become stiffer. The same phenomenon occurs with the downstream sensor (14) and the vibration unit (12).

Figure 30 (3) shows the stiffness change rate aK (301g) and the thickness change rate rt (301f). They were obtained with a variation of less than 0.01%. In the thickness stiffness processing according to the embodiment, the sensor amplitude information is not used, so the stiffness change rate aK (301g) and the thickness change rate rt (301f) can be measured regardless of the sensitivity change of the sensor (13, 14) or the vibration unit (12).

(4-2-3. Thickness and rigidity diagnosis result 3)
A description will be given of a thickness/rigidity diagnosis result 3 with reference to Fig. 31 and Fig. 32. Fig. 31 and Fig. 32 are diagrams showing an example of a thickness/rigidity diagnosis result 3 according to an embodiment. In the following, a test for verifying adhesion diagnosis was performed as the thickness/rigidity diagnosis process.

Figure 31 (1) shows the results of density calibration with a total of 0.978 g of vinyl tape attached to the outside of the vibrating tube. "Normal" shows the case where no tape was attached, and "Tape" shows the case where tape was attached. The frequency and temperature were measured in air and water for each case. The frequency was corrected and the density was calculated based on the temperature. Each measurement was performed five times.

Figures 31 (2) and 31 (3) show the results of determining the density measurement coefficient Cd (28k) and density measurement coefficient fa (28l) from Figure 31 (1). The density error Δρ0 (201d) was calculated with the measurement object density ρt (202c) being air and water. By attaching tape to the outside, the density measurement coefficient fa decreased and the density measurement coefficient Cd increased. The density error Δρ0 (201d) is in g/l. By attaching tape to the outside, the density error Δρ0 (201d) increases. This is thought to be due to the increased weight.

Figure 32 shows the thickness diagnosis results. The amount of change was calculated based on the value of Test #1. The inner diameter dc (301c) is the value calculated using the above formula (42), the thickness tc (301d) is the value calculated using the above formula (43), the thickness change dt (301e) is the value calculated using the above formula (44), the thickness change rate rt (301f) is the value calculated using the above formula (45), and the stiffness change rate aK (301g) is the result calculated using the above formula (46). When adhesion occurs, the density measurement coefficient Cd (28k) and the density measurement coefficient fa (28l) fluctuate, so adhesion diagnosis is possible by density calibration.

(4-2-4. Effects)
As described above, in the thickness stiffness diagnosis process according to the embodiment, the thickness and stiffness change rate can be determined individually by using the change in density measurement coefficient obtained by density calibration and the design information of the vibrating tube. Since the thickness information and stiffness change rate can be determined individually, corrosion diagnosis and adhesion diagnosis are possible. Furthermore, instead of judging corrosion from stiffness change, the thickness change is diagnosed directly. A fluctuation tolerance value is set for the thickness information and stiffness change rate, and an abnormality can be notified by issuing an alarm. At this time, the thickness information includes the inner diameter, thickness, thickness change, and thickness change rate, and the allowable value for abnormality judgment is set as a value directly related to the abnormality.

In addition, in the thickness/stiffness diagnostic process according to the embodiment, thickness information and stiffness change rate are obtained using the change in density measurement coefficient obtained by density calibration and the design information of the vibration tube, so new mechanisms such as fixing the drive gain or obtaining a frequency response are not required. In this case, special operations and software for analysis are not required. Also, the diagnostic function can be realized not only by the conversion unit (20) of the Coriolis mass flowmeter (1) but also by the external device (31) or calibration device (3). Diagnosis is possible along with the calibration of the Coriolis mass flowmeter (1). The soundness of the device is diagnosed by adding a diagnostic procedure after the density calibration procedure.

In conventional diagnosis based on stiffness change, the amplitude of the sensor signal is used in addition to the frequency. In this case, it is affected by the sensitivity of the sensor, etc. In the thickness stiffness diagnosis process according to the embodiment, the sensor amplitude information is not used, so the stiffness change rate and thickness change are estimated individually regardless of changes in the sensitivity of the sensor or vibration unit, or changes in the circuit gain.

(4-3. Flow rate diagnosis results and effects)
The flow rate diagnosis results and effects will be described with reference to Figures 33 to 36. Below, flow rate diagnosis result 1 and flow rate diagnosis result 2 will be described, and then the effects of the flow rate error diagnosis and simple correction process will be described.

(4-3-1. Flow rate diagnosis result 1)
The flow rate diagnosis result 1 will be described with reference to Fig. 33. Fig. 33 is a diagram showing an example of the flow rate diagnosis result 1 according to the embodiment.

First, consider a situation in which corrosion increases the flow rate error. Corrosion reduces the flow rate measurement coefficient Cq and increases the ratio θ0/f of the phase difference θ0 and the frequency f. An error occurs because the flow rate measurement coefficient Cq (28f) is the value before corrosion.

Figure 33 shows the relationship between error and simple correction. If the error variation per measurement is -0.1%, then after 10 measurements, the error will be -1.0%. If the initial value of the flow measurement coefficient Cq (28f) is continued to be used, an error of +1.0% will be produced in the 10th flow measurement.

"Qe = -0.1%" shows the flow rate error when no flow rate calibration is performed. The flow rate error was calculated when the flow rate correction coefficient fk (28u) is updated. "fk = -0.1%" shows the flow rate error when the rate of change of the flow rate correction coefficient fk (28u) is equal to the flow rate error. In this case, the flow rate measurement coefficient Cq (28f) can be corrected by using the flow rate correction coefficient fk (28u). The flow rate error returns to zero by performing density calibration.

The error when the rate of change of the flow correction coefficient fk (28u) is -0.05%/calibration is shown as "fk = -0.05%". When it is -0.15%/calibration, it is shown as "fk = -0.15%". The error can be suppressed by simple correction. If the allowable error is ±0.5%, without simple correction, the allowable error is reached after 5 tries, but with simple correction, it becomes 10 tries. This shows that the interval between flow calibrations can be extended by using the flow correction coefficient fk (28u) and performing simple correction of the flow measurement coefficient.

In this way, simple flow correction is possible by updating the flow correction coefficient fk (28u) based on the density calibration results.

(4-3-2. Flow rate diagnosis result 2)
The flow rate diagnosis result 2 will be described with reference to Fig. 34 to Fig. 36. Fig. 34 to Fig. 36 are diagrams showing an example of the flow rate diagnosis result 2 according to the embodiment.

Figure 34 (1) shows the rate of change of density measurement coefficient, rate of change of stiffness, rate of change of thickness, and flow rate error when corrosion was repeated multiple times. At the same time as the density calibration experiment in Figure 27 (1), water was run and the flow rate error rate Qe was measured. The coefficient change rate aCd and the coefficient change rate afa show the change ratio of the density measurement coefficient obtained in Figure 27 (2). The coefficient change rate aCd (201e) shows the rate of change of density measurement coefficient Cdc (151a). The coefficient change rate afa (201f) shows the rate of change of density measurement coefficient fac (151b). The inner diameter change rate rt shows the rate of change of thickness rt (301f) calculated in the thickness stiffness diagnosis in Figure 28 (1). The stiffness change rate aK shows the stiffness change rate aK (301g) calculated in the thickness stiffness diagnosis in Figure 28 (1). The change in the flow measurement coefficient Cq (28f) was calculated from the flow error rate Qe, and the change rate was aCq.

Figure 34 (2) shows the relationship between the rate of change of the density measurement coefficient, the rate of change of the wall thickness, the rate of change of the stiffness, and the change in the flow coefficient Cq. The flow error Qe indicates the error rate when the flow measurement coefficient Cq (28f) is measured without updating it. If the flow correction coefficient fk (28u) has the same trend as the rate of change aCq, the flow error can be corrected. The trends of the rate of change aCq and each rate of change match, but differences appear as the corrosion increases. The change in the coefficient rate of change afa is small. The change in the flow measurement coefficient Cq (28f) can be easily corrected using at least one of the coefficient rate of change aCd, the rate of change of the wall thickness rt, and the rate of change of the stiffness aK.

Figure 34 (3) shows the results of the flow error diagnosis simple correction process according to the embodiment using the results of Figure 34 (1). The flow error when simple correction is not performed is shown in Qe. The flow error when simple correction is performed using the stiffness change rate aK (301g), the wall thickness change rate rt (301f), the coefficient change rate aCd (201e), and the coefficient change rate afa (201f) is shown. In the above-mentioned (56) formula, one of Ckx (x = 1 to 4) is set to 1, the others are set to 0, and each change rate is set to the flow correction coefficient fk (28u). Other than the flow error Qe, the results are shown before and after updating the flow correction coefficient fk (28u). When the coefficient change rate afa (201f) is used, the effect is small. This is because the change in the coefficient change rate afa (201f) is smaller than the change in the flow measurement coefficient Cq (28f). The results using the other three parameters are equivalent. Because the rate of change is greater than that of the flow measurement coefficient Cq (28f), the flow error after simple correction becomes negative with each iteration.

Figure 34 (4) shows the relationship between the flow measurement coefficient Cq (28f) and the wall thickness change rate rt (301f), stiffness change rate aK (301g), coefficient change rate aCd (201e), and coefficient change rate afa (201f). There is a correlation between all variables. The slope of the coefficient change rate afa (201f) is small.

Figure 35 (1) shows the results of determining the flow correction coefficient Ckx (28v) using multiple regression analysis. A blank indicates a value of 0. The results show the case where the four parameters are used independently, and the case where the correction coefficient is determined by combining the stiffness change rate aK (301g) and the wall thickness change rate rt (301f), the coefficient change rate aCd (201e) and the coefficient change rate afa (201f). Correlation is high in all cases. Although the combination and F value become small, the combination is also effective. The flow correction coefficient fk (28u) can be calculated using the coefficient change rate aCd (201e), the wall thickness change rate rt (301f), the stiffness change rate aK (301g) and the wall thickness change rate rt (301f), or the coefficient change rate aCd (201e) and the coefficient change rate afa (201f), allowing for simple correction of the mass flow rate.

Figure 35 (2) shows the flow rate correction result when the flow rate correction coefficient Ckx (28v) in Figure 35 (1) is used. By performing density calibration, the error returns to almost zero. By updating the flow rate correction coefficient fk (28u) using the density calibration result, simple correction of the flow rate is possible.

Figure 36 (1) shows the results of estimating the flow rate error. The flow rate correction coefficient fk (28u) was found from the above formula (56), and the flow rate error rate rqe (501b) was calculated from the above formula (59). One of the four variables was used for the flow rate correction coefficient fk (28u). Shown here is the result rqex1 when the flow rate correction coefficient Ckx (28v) corresponding to the variable used in the above formula (56) is set to the value 1.0, and the result rqex2 when the flow rate correction coefficient Ckx (28v) is used using the value found by correlation.

Figure 36 (2) shows the change in flow rate error Qe and flow rate error rate rqex1. The change resulting from using the coefficient change rate afa (201f) is small. The flow rate error rate rqe (501b) calculated using the stiffness change rate aK (301g), the wall thickness change rate rt (301f) and the coefficient change rate aCd (201e) shows the same change trend as the flow rate error Qe.

Figure 36 (3) shows the change in flow error Qe and flow error rate rqex2. The change trend of each result was consistent with that of the flow error Qe.

By setting a flow rate error alarm value (502r) for the flow rate error rate rqe (501b), it is possible to determine whether the flow rate diagnosis is abnormal (501r).

(4-3-3. Effects)
As described above, in the flow rate error diagnosis and simple correction process according to the embodiment, the flow rate measurement coefficient and the flow rate error can be obtained by using the stiffness change rate, thickness change rate, and density measurement coefficient change rate obtained from the density calibration, density diagnosis process, and thickness stiffness diagnosis process. By using these, the flow rate measurement coefficient is simply corrected, thereby reducing the flow rate error without flow rate calibration.

Density calibration can be accomplished on-site by measuring frequency and temperature in known fluids such as air and water. Simple correction of the flow correction factor extends the actual calibration interval.

There is a high correlation between the mass flow rate error and the rate of change of stiffness, wall thickness, and density measurement coefficient, but there is a difference in the slope. By correcting the relationship between the mass flow rate error and each rate of change with an approximate straight line or curve, the error of the simplified correction is reduced. The parameters and correction coefficients used are determined using multiple regression analysis, AI inference, etc.

The accuracy of the simple correction depends on the measurement accuracy of the parameters used in the correction formula for the flow correction coefficient. Since density calibration can be performed in a stable environment, it can be calculated with high accuracy.

The flow rate error is estimated from the change in the flow rate correction coefficient. A tolerance is set for the flow rate error, and an alarm is issued to notify of any abnormalities.

Changing the flow correction coefficient creates discontinuities in the mass flow measurement results. If the flow rate fluctuation caused by changing the flow correction coefficient is within the acceptable range, you can choose to prioritize the continuity of the measurement value. Setting a flow rate fluctuation tolerance determines whether or not the flow correction coefficient can be replaced, and suppresses fluctuations in the mass flow measurement results.

Coriolis mass flowmeters are characterized by their ability to provide highly accurate measurements. Mass flow measurement is one of the basic functions of a Coriolis mass flowmeter, and the target accuracy is maintained by monitoring flow rate errors.

(4-4. Timing prediction diagnosis results)
The timing prediction diagnostic result and the effect will be described with reference to Fig. 37. In the following, the timing prediction diagnostic result will be described, and then the effect of the timing prediction diagnostic process will be described.

(4-4-1. Timing prediction diagnosis results)
An example of calculation of timing prediction diagnosis is shown in Fig. 37. Fig. 37 is a diagram showing an example of a timing prediction diagnosis result according to the embodiment.

Two points were assumed for each date and time, drive time, accumulated flow rate, and density error. These are shown in "Data 1" and "Data 2". The coefficients of the approximate line were calculated using the above formulas (64) to (69) and are shown in "Slope ax" and "Intercept bx". The diagnostic target value dts is -0.5 mm. The predicted value was calculated using the above formulas (70) to (72) and is shown in "Estimation". "Estimation - Data 2" shows the predicted value from "Data 2". In FIG. 37, from "Data 2", the diagnostic target value dts is reached after 8 days, drive time of 60 hours, or accumulated flow rate of 760 t.

(4-4-2. Effects)
As described above, timing prediction diagnosis makes it possible to predict when a failure will occur or when maintenance or equipment replacement will be required. By having a history of calibration and diagnosis, the health of the equipment can be understood. By using the converter's operating time and integrated flow rate in addition to the time, a diagnosis that is close to reality can be performed. Corrosion occurs when corrosive fluids are flowed, so the integrated flow rate is important. Converter failures are often affected by the operating time. By evaluating density error and flow rate error, it is possible to predict when flow rate calibration will be necessary. By storing the obtained diagnosis results in a history, the state of condition changes can be understood. This makes timing prediction diagnosis (life diagnosis) possible. From multiple parameters, the parameter that suits the purpose can be used.

For users, predicting when maintenance or replacement is necessary is important for the effective use of equipment. Maintenance requires the equipment to be shut down and calibration costs are incurred. For equipment prone to breakdowns such as corrosion, replacement must be anticipated.

5. Flow of each process of the calibration device (3) and the diagnosis device (2)
38 to 43, the flow of each process of the calibration device (3) and the diagnosis device (2) according to the embodiment will be described. Below, the flow of the entire diagnosis process according to the embodiment will be described, followed by the flow of the density calibration process as the flow of the calibration device (3), and the flow of the density error diagnosis process, the flow of the wall thickness stiffness diagnosis process, the flow of the flow rate error diagnosis/simple correction process, and the flow of the timing prediction diagnosis process as the flow of the diagnosis device (2).

(5-1. Overall flow of diagnostic processing)
The flow of the entire diagnostic process will be described with reference to Fig. 38. Fig. 38 is a flowchart showing an example of the flow of the entire diagnostic process according to the embodiment. Note that the processes of steps S101 to S105 below can be executed in a different order. Also, some of the processes of steps S101 to S105 below may be omitted.

First, the calibration device (3) executes density calibration processing (step S101). Next, the diagnosis device (2) executes density error diagnosis processing (step S102), thickness stiffness diagnosis processing (step S103), flow rate error diagnosis and simple correction processing (step S104), timing prediction diagnosis processing (step S105), and ends the processing.

(5-2. Density calibration process flow)
The flow of the entire diagnosis process will be described with reference to FIG. 39. FIG. 39 is a flowchart showing an example of the flow of the entire density calibration process according to the embodiment. Below, the flow of the entire density calibration process will be described, and then the flow of each process will be described. Note that each of the processes below can also be executed in a different order. Also, some of the processes below may be omitted.

(5-2-1. Overall flow of density calibration process)
As shown in FIG. 39, the calibration device (3) executes a density measurement coefficient calculation process (steps S201 to S223), stores the density measurement coefficient in the parameter (28) (step S224), and ends the process.

(5-2-2. Overall flow of density measurement coefficient calculation process)
The calibration device (3) calibrates the density measurement and updates the density measurement coefficient as shown below. First, the frequency is measured for two types of materials with known densities. At this time, the coefficient n (152c) is used to perform two measurements, and the coefficient n (152c) is set to 1 as an initial value (step S201). Next, the calibration device (3) sets the filling state to On in order to determine that the material in the vibration tube has been replaced (step S202). Next, the calibration device (3) determines whether the filling state is On (step S203). At this time, the calibration device (3) waits until the material n is filled into the vibration tube (11). If the filling state is On (step S203: Yes), the calibration device (3) proceeds to the process of step S204, and if the filling state is not On (step S203: No), the calibration device (3) proceeds to the process of step S206.

The calibration device (3) fills the vibrating tube (11) with the substance n (step S204). At this time, an external device different from the Coriolis mass flowmeter (1) empties the vibrating tube (11) in the case of air, and in the case of a vacuum, discharges the substance inside using a vacuum pump or the like. Here, the density calibration process requires the density of the substance n, and if the density changes with temperature and pressure, a formula or a mathematical table related to temperature and pressure is required. Then, the display operation unit (30) or the external device (31) turns off filling to indicate that filling has ended (step S205), and the process returns to step S203.

The calibration device (3) waits until the measured values stabilize, since the temperature and other parameters become unstable due to the replacement of the substance (step S206). At this time, the calibration device (3) may wait for a fixed period of time, or may monitor fluctuations in the frequency f (28c) and temperature T (28e), or may not wait if the fluctuations do not affect the results. The calibration device (3) then acquires the frequency f (28c) and temperature T (28e) (step S207) and proceeds to the processing of step S208.

The calibration device (3) determines whether the pressure gauge (29) is connected based on the pressure gauge connection signal (28s) (step S208). At this time, if the pressure gauge (29) is connected (step S208: Yes), the calibration device (3) acquires the external input pressure Pin (28r) and sets it as pressure P (28t) (step S210), and proceeds to the process of step S211. On the other hand, if the pressure gauge (29) is not connected (step S208: No), the calibration device (3) sets the default pressure Ps (28q) as pressure P (28t) (step S209), and proceeds to the process of step S211.

The calibration device (3) uses the frequency correction unit (53) to correct the frequency f (28c) with the temperature T (28e) and pressure P (28t) and calculates the corrected frequency fn (153) (step S211). The calibration device (3) also uses the material selection switch (54) to store the corrected frequency fn (153) in the corrected frequency f1 (154) or the corrected frequency f2 (155) according to the coefficient n (152c) (step S212). The calibration device (3) also uses the standard density calculation unit (55) to calculate the standard density ρc (156) of the material n from the temperature T (28e), pressure P (28t) and coefficient n (152c) (step S213), and proceeds to the processing of step S214.

The calibration device (3) uses the density selection switch (56) to determine whether the density ρn (157) is to be manually input by density selection (152b) (step S214). At this time, if the calibration device (3) determines that the density is to be manually input (step S214: Yes), the calibration device (3) sets the manually input density ρin (152a) set by the display operation unit (30) or the external device (31) as the density ρn (157) (step S215) and proceeds to the process of step S217. On the other hand, if the calibration device (3) determines that the density is not to be manually input (step S214: No), the calibration device (3) sets the standard density ρc (156) as the density ρn (157) (step S216) and proceeds to the process of step S217.

The calibration device (3) uses the material selection switch (57) to store the density ρn (157) in the density ρ1 (158) or density ρ2 (159) according to the coefficient n (152c) (step S217). The calibration device (3) also sets the coefficient n (152c) to n+1 (step S218). If the coefficient n (152c) is 2 or less (step S219: Yes), the calibration device (3) proceeds to the processing of step S208 and measures the second material. On the other hand, if the coefficient n (152c) is greater than 2 (step S219: No), the calibration device (3) uses the density measurement coefficient calculation execution unit (58) to calculate the density measurement coefficient Cdc (151a) and the density measurement coefficient fac (151b) (step S220). At this time, the calibration device (3) calculates the density measurement coefficient by substituting the corrected frequency f1 (154), the corrected frequency f2 (155), the density ρ1 (158), and the density ρ2 (159) into the above-mentioned equations (21) to (24).

The calibration device (3) saves the date and time, the converter drive time, and the accumulated flow rate (step S221). At this time, the calibration device (3) saves the date and time (28x) in the calibration date and time (151x), the converter drive time (28y) in the drive time (151y), and the accumulated flow rate (28z) in the accumulated flow rate (151z).

The calibration device (3) sets the update flag (151s) (step S222), sets the density calibration completion signal (160) (step S223), and proceeds to processing in step S224.

(5-3. Flow of Density Error Diagnosis Processing)
The flow of density error diagnosis processing will be described with reference to Fig. 40. Fig. 40 is a flowchart showing an example of the overall flow of density error diagnosis processing according to an embodiment. Below, the overall flow of density error diagnosis processing will be described, and then the flow of each process will be described. Note that each process below can also be executed in a different order. Also, some of the processes below may be omitted.

(5-3-1. Overall flow of density error diagnosis process)
As shown in Fig. 40, the diagnostic device (2) executes an initialization determination process (steps S301 to S307), and if the initialization signal (203) is set (step S308: Yes), it executes a density error initialization process (step S309) and ends the process. On the other hand, if the initialization signal (203) is not set (step S308: No), the diagnostic device (2) proceeds to the process of step S310.

If the calculation judgment signal (204) is set (step S310: Yes), the diagnostic device (2) executes density error calculation judgment processing (step S311) and ends the processing. On the other hand, if the calculation judgment signal (204) is not set (step S310: No), the diagnostic device (2) ends the processing.

(5-3-2. Flow of initialization determination process)
As shown in FIG. 40, after the calibration device (3) performs density calibration processing (step S301) of the density measurement coefficient, the diagnostic device (2) selects the processing to be performed based on the density calibration completion signal (160) and the density diagnosis setting value (202).

The diagnostic device (2) resets the initialization signal (203) and the calculation judgment signal (204) (step S302). Next, the diagnostic device (2) judges whether the density calibration completion signal (160) is set (step S303). At this time, if the density calibration completion signal (160) is set (step S303: Yes), the diagnostic device (2) proceeds to the process of step S304. On the other hand, if the density calibration completion signal (160) is not set (step S303: No), the diagnostic device (2) ends the process.

The diagnostic device (2) determines whether the initialization execution command (202u) is set (S304). At this time, if the initialization execution command (202u) is set (step S304: Yes), the diagnostic device (2) sets the initialization signal (203) (step S305) and proceeds to processing from step S308 onwards. On the other hand, if the initialization execution command (202u) is not set (step S304: No), the diagnostic device (2) proceeds to processing of step S305.

The diagnostic device (2) judges whether an initial value exists (step S305). If there is no initial value (step S305: Yes), the diagnostic device (2) sets the initialization signal (203) (step S306) and proceeds to processing from step S308 onwards. On the other hand, if there is an initial value (step S305: No), the diagnostic device (2) sets the calculation judgment signal (204) (step S307) and proceeds to processing from step S308 onwards. Here, the diagnostic device (2) judges that there is no initial value when the initial coefficient Cd0 (202a) is 0, the initial coefficient fa0 (202b) is 0, or the initial date and time (202x) is not set.

(5-3-3. Flow of density error initialization process)
The diagnostic device (2) saves the density calibration result (151) in the parameter (28), sets the initial value of the density diagnosis setting value (202), resets the initialization execution command (202u), initializes the density diagnosis result (201), sets the initialization flag (201t), sets the update flag (201s), resets the density calibration completion signal (160), sets the density diagnosis completion signal (210), and ends the process.

(5-3-4. Flow of Density Error Calculation and Determination Process)
The diagnostic device (2) calculates density fluctuation Δρ (201c), density error Δρ0 (201d), coefficient change rate aCd (201e), and coefficient change rate afa (201f) as density diagnostic results (201) from the change in density measurement coefficient. At this time, the diagnostic device (2) sets the coefficient selection signal (205) if the absolute value of the density fluctuation Δρ (201c) is greater than the density fluctuation allowable value (202d). On the other hand, the diagnostic device (2) resets the coefficient selection signal (205) if the absolute value of the density fluctuation Δρ (201c) is equal to or less than the density fluctuation allowable value (202d).

The diagnostic device (2) determines whether the coefficient selection signal (205) is set. At this time, if the coefficient selection signal (205) is set, the density calibration result (151) is set to the parameter (28). On the other hand, if the coefficient selection signal (205) is set, the diagnostic device (2) proceeds to the next process.

The diagnostic device (2) sets the measurement coefficient and the measurement information in the density diagnosis result (201). The diagnostic device (2) also compares the change in density error Δρ0 (201d) with the density error warning value (202h) and sets a density error abnormality (201h), compares the change in coefficient change rate aCd (201e) with the coefficient change rate aCd allowable value (202i) and sets a coefficient change rate aCd abnormality (201i), and compares the change in coefficient change rate afa (201f) with the coefficient change rate afa allowable value (202j) and sets a coefficient change rate afa abnormality (201j).

The diagnostic device (2) resets the initialization flag (201t), sets the update flag (201s), resets the density calibration completion signal (160), sets the density diagnosis completion signal (210), and ends the process.

(5-4. Flow of thickness and stiffness diagnosis process)
The flow of the wall thickness stiffness diagnosis process will be described with reference to FIG. 41. FIG. 41 is a flowchart showing an example of the flow of the entire wall thickness stiffness diagnosis process according to the embodiment. Below, the flow of the entire wall thickness stiffness diagnosis process will be described, and then the flow of each process will be described. Note that each of the processes below can also be executed in a different order. Also, some of the processes below may be omitted.

(5-4-1. Overall flow of thickness and stiffness diagnosis process)
As shown in Fig. 41, the diagnostic device (2) executes an initialization determination process (steps S401 to S407), and if the initialization signal (306) is set (step S408: Yes), it executes a thickness/stiffness diagnosis initialization process (step S409) and ends the process. On the other hand, if the initialization signal (306) is not set (step S408: No), the diagnostic device (2) proceeds to the process of step S410.

If the diagnostic initialization signal (307) is set (step S410: Yes), the diagnostic device (2) executes thickness stiffness calculation processing (step S411), executes thickness stiffness change initialization processing (step S412), and ends the processing. On the other hand, if the diagnostic initialization signal (307) is not set (step S410: No), the diagnostic device (2) proceeds to processing in step S413.

When the diagnosis execution signal (308) is set (step S413: Yes), the diagnosis device (2) executes a thickness stiffness calculation process (step S414), executes a thickness stiffness change determination process (step S415), and ends the process. On the other hand, when the diagnosis execution signal (308) is not set (step S413: No), the diagnosis device (2) ends the process.

(5-4-2. Flow of initialization determination process)
As shown in Fig. 41, first, the diagnostic device (2) resets the initialization signal (306), the diagnostic initialization signal (307), and the diagnostic execution signal (308) (step S401). Next, the diagnostic device (2) judges whether the density diagnosis completion signal (210) is set (step S402). At this time, if the density diagnosis completion signal (210) is set (step S402: Yes), the diagnostic device (2) proceeds to the process of step S403, and if the density diagnosis completion signal (210) is not set (step S402: No), the diagnostic device (2) ends the process.

The diagnostic device (2) determines whether an initial value exists (step S403). At this time, if there is no initial value (step S403: Yes), the diagnostic device (2) sets the initialization signal (306) (step S404). On the other hand, if there is an initial value (step S403: No), the diagnostic device (2) proceeds to the process of step S405. Here, the diagnostic device (2) determines that there is no initial value when either the initial inner diameter d0 (302c) is the numerical value 0 or the initial date and time (302x) has not been set.

The diagnostic device (2) determines whether the initialization execution command (302u) is set (step S405). At this time, if the initialization execution command (302u) is set (step S405: Yes), the diagnostic initialization signal (307) is set (step S406) and the process proceeds to step S408 and subsequent steps. On the other hand, if the initialization execution command (302u) is not set (step S405: No), the diagnostic device (2) sets the diagnostic execution signal (308) (step S407) and the process proceeds to step S408 and subsequent steps.

(5-4-3. Flow of wall thickness and stiffness diagnosis initialization process)
The diagnostic device (2) sets an initial value to the thickness stiffness diagnosis setting value (302), resets the initialization execution command (302u), initializes the thickness stiffness diagnosis result (301), sets the initialization flag (301t), sets the update flag (301s), resets the density diagnosis completion signal (210), sets the thickness stiffness diagnosis completion signal (310), and terminates the processing.

(5-4-4. Flow of wall thickness stiffness calculation process)
The diagnostic device (2) calculates the thickness change rate, calculates the stiffness change rate, sets the diagnostic information of the thickness stiffness diagnostic result (301), and ends the process.

(5-4-5. Flow of Initialization Process for Thickness and Stiffness Change)
The diagnostic device (2) sets the initial value of the thickness stiffness diagnosis setting value (302), resets the initialization execution command (302u), initializes the thickness stiffness diagnosis result (301), sets the initialization flag (301t), sets the update flag (301s), resets the density diagnosis completion signal (210), sets the thickness stiffness diagnosis completion signal (310), and terminates the processing.

(5-4-6. Flow of thickness stiffness change determination process)
The diagnostic device (2) compares the wall thickness stiffness diagnosis result (301) and the density diagnosis result (201) with the wall thickness stiffness diagnosis setting value (302), sets the diagnostic abnormality information in the wall thickness stiffness diagnosis result (301), resets the initialization flag (301t), sets the update flag (301s), resets the density diagnosis completion signal (210), sets the wall thickness stiffness diagnosis completion signal (310), and terminates the processing.

(5-5. Flow of flow rate error diagnosis and simple correction process)
The flow of the flow error diagnosis and simple correction process will be described with reference to FIG. 42. FIG. 42 is a flowchart showing an example of the overall flow of the flow error diagnosis and simple correction process according to the embodiment. Below, the overall flow of the flow error diagnosis and simple correction process will be described, and then the flow of each process will be described. Note that each of the processes below can also be executed in a different order. Also, some of the processes below may be omitted.

(5-5-1. Overall flow of flow rate error diagnosis and simple correction process)
As shown in Fig. 42, first, the diagnostic device (2) executes an initialization determination process (steps S501 to S509), and if the initialization execution signal 1 (507) is set (step S510: Yes), it executes a flow rate initialization process (step S511) and ends the process. On the other hand, if the initialization execution signal 1 (507) is not set (step S510: No), the diagnostic device (2) proceeds to the process of step S512.

If the initialization execution signal 2 (508) is set (step S512: Yes), the diagnostic device (2) executes the rigidity thickness initialization process (step S513) and ends the process. On the other hand, if the initialization execution signal 2 (508) is not set (step S512: No), the diagnostic device (2) proceeds to the process of step S514.

If the update execution signal (509) is set (step S514: Yes), the diagnostic device (2) executes the flow correction coefficient update process (step S515) and ends the process. On the other hand, if the update execution signal (509) is not set (step S514: No), the diagnostic device (2) ends the process.

(5-5-2. Flow of initialization determination process)
As shown in FIG. 42, first, the diagnostic device (2) resets the initialization execution signal 1 (507), the initialization execution signal 2 (508), and the update execution signal (509) (step S501). Next, the diagnostic device (2) judges whether the flow rate calibration completion signal (120) is set (step S502). Here, the flow rate calibration completion signal (120) is set when the mass flow rate calibration process is executed by the mass flow rate calibration unit (41) of the calibration device (3). At this time, if the flow rate calibration completion signal (120) is set (step S502: Yes), the diagnostic device (2) sets the initialization execution signal 1 (507) (step S503) and proceeds to the process of step S510 and after. On the other hand, if the flow rate calibration completion signal (120) is not set (step S502: No), the diagnostic device (2) proceeds to the process of step S504.

The diagnostic device (2) determines whether the thickness stiffness diagnosis completion signal (310) is set (step S504). At this time, if the thickness stiffness diagnosis completion signal (310) is set (step S504: Yes), the process proceeds to step S505, and if the thickness stiffness diagnosis completion signal (310) is not set (step S504: No), the process ends. Here, the thickness stiffness diagnosis completion signal (310) is set when the thickness stiffness diagnosis process is executed by the thickness stiffness diagnosis unit (70).

The diagnostic device (2) determines whether an initial value exists (step S505). Here, the diagnostic device (2) determines whether an initial date and time (502x) has been set. At this time, if an initial value does not exist (step S505: Yes), the diagnostic device (2) sets the initialization execution signal 2 (508) (step S508) and proceeds to processing from step S510 onwards. On the other hand, if an initial value exists (step S505: No), the diagnostic device (2) proceeds to processing of step S506.

The diagnostic device (2) determines whether the initialization flag (301t) is set (step S506). At this time, if the initialization flag (301t) is set (step S506: Yes), the diagnostic device (2) sets the initialization execution signal 2 (508) (step S508) and proceeds to processing from step S510 onwards. On the other hand, if the initialization flag (301t) is not set (step S506: No), the diagnostic device (2) proceeds to processing of step S507.

The diagnostic device (2) determines whether the initialization execution command (502u) is set (step S507). At this time, if the initialization execution command (502u) is set (step S507: Yes), the diagnostic device (2) sets the initialization execution signal 2 (508) (step S508) and proceeds to processing from step S510 onwards. On the other hand, if the initialization execution command (502u) is not set (step S507: No), the diagnostic device (2) sets the update execution signal (509) (step S509) and proceeds to processing from step S510 onwards.

(5-5-3. Flow of flow rate initialization process)
The diagnostic device (2) initializes the flow diagnosis setting value (502), sets an initialization execution command (502u), sets the flow correction coefficient fk (28u) to an initial value of 1.0, initializes the flow diagnosis result (501), resets the flow diagnosis abnormality (501r), sets the initialization flag (501t), sets the update flag (501s), resets the flow calibration completion signal (120), and ends the process.

(5-5-4. Flow of rigidity thickness initialization process)
The diagnostic device (2) initializes the flow rate diagnosis setting value (502), resets the initialization execution command (502u), sets the flow rate correction coefficient fk (28u) to an initial value of 1.0, initializes the flow rate diagnosis result (501), resets the flow rate diagnosis abnormality (501r), sets the initialization flag (501t), sets the update flag (501s), resets the thickness/stiffness diagnosis completion signal (310), and ends the process.

(5-5-5. Flow of flow rate correction coefficient update process)
The diagnostic device (2) calculates the flow correction coefficient, the flow error rate, and the flow rate fluctuation rate. At this time, if the absolute value of the flow rate fluctuation rate rqd (501c) is greater than the flow rate fluctuation allowable value (502h), the diagnostic device (2) sets the flow coefficient selection signal (504) and sets the flow correction coefficient fk (28u). Also, if the absolute value of the flow rate error rate rqe (501b) is greater than the flow rate error alarm value (502r), the diagnostic device (2) sets a flow rate diagnosis abnormality (501r). On the other hand, if the absolute value of the flow rate error rate rqe (501b) is equal to or less than the flow rate error alarm value (502r), the diagnostic device (2) resets the flow rate diagnosis abnormality (501r).

The diagnostic device (2) resets the initialization flag (501t), sets the update flag (501s), resets the thickness stiffness diagnosis completion signal (310), and ends the process.

(5-6. Flow of timing prediction diagnosis process)
The flow of the timing prediction diagnosis process will be described with reference to Fig. 43. Fig. 43 is a flowchart showing an example of the flow of the entire timing prediction diagnosis process according to the embodiment. Note that the processes of steps S601 to S605 below can be executed in a different order. Also, some of the processes of steps S601 to S605 below may be omitted.

The diagnostic device (2) determines whether an update flag is set (step S601). At this time, if an update flag is set (step S601: Yes), the diagnostic device (2) proceeds to the process of step S602. On the other hand, if none of the update flags are set (step S601: No), the diagnostic device (2) ends the process. Note that the update flag of the diagnostic data is included in the result of each diagnosis.

The diagnostic device (2) checks the density calibration result (151), density diagnosis result (201), thickness stiffness diagnosis result (301), and flow rate diagnosis result (501), imports the diagnosis result data (step S602), calculates a change trend value (601) from the imported data (step S603), calculates a timing prediction diagnosis result (603) from the change trend value (601) and the diagnosis target value (602) (step S604), resets the update flag (step S605), and ends the process.

6. Effects of the embodiment
Finally, effects of the embodiment will be described below: Effects 1 to 7 corresponding to the processing according to the embodiment will be described below.

(6-1. Effect 1)
In the process according to the embodiment described above, a density diagnostic result (201) relating to the density error of the fluid before and after the density calibration is generated based on a density calibration result (151) relating to the calibration of the density of the fluid generated by calibrating the Coriolis mass flowmeter (1) that measures the flow rate and density of the fluid flowing through the vibrating tube (11) based on the Coriolis force acting on the vibrated vibrating tube (11), and a calculation is performed on at least one of the thickness and rigidity of the vibrating tube (11) based on the density diagnostic result (201) to generate a thickness rigidity diagnostic result (301) relating to the change in the vibrating tube (11). Therefore, in this process, the state of the vibrating tube (11) of the Coriolis mass flowmeter (1) can be accurately diagnosed.

(6-2. Effect 2)
In the process according to the embodiment described above, a density error is calculated using the initial density measurement coefficient, the density measurement coefficient indicated by the density calibration result (151), and the density of the object to be measured, and a thickness and stiffness diagnosis result (301) including at least one of the results related to the thickness change and stiffness change of the vibration tube (11) is generated using the change rate of the density measurement coefficient indicated by the density diagnosis result (201) and the design value of the vibration tube (11), and an abnormality related to the vibration tube (11) is detected when the thickness and stiffness diagnosis result (301) is equal to or greater than a threshold value. Therefore, in this process, the density diagnosis result (201) and the thickness and stiffness diagnosis result (301) are effectively generated, thereby making it possible to accurately diagnose the state of the vibration tube (11) of the Coriolis mass flowmeter (1).

(6-3. Effect 3)
In the process according to the embodiment described above, a thickness/rigidity diagnosis result (301) is generated that includes at least one of the inner diameter, thickness, thickness change, thickness change rate, rigidity change rate, corrosion diagnosis, and adhesion diagnosis of the vibration tube (11). Therefore, in this process, the thickness/rigidity diagnosis result (301) is effectively used to accurately diagnose the state of the vibration tube (11) of the Coriolis mass flowmeter (1).

(6-4. Effect 4)
In the process according to the embodiment described above, a calculation related to the flow rate of the fluid is performed based on the thickness/rigidity diagnosis result (301) to generate a flow rate diagnosis result (501) related to the flow rate error of the fluid. Therefore, in this process, by generating the flow rate diagnosis result (501), it is possible to accurately diagnose the state of the vibrating tube (11) of the Coriolis mass flowmeter (1) and perform a simple correction related to the flow rate.

(6-5. Effect 5)
In the process according to the embodiment described above, a flow correction coefficient is calculated using at least one of the stiffness change rate, the wall thickness change rate, and the change rate of the density measurement coefficient, and based on the calculated flow correction coefficient, update control of the flow correction coefficient used by the Coriolis mass flowmeter (1) to measure the flow rate is performed. In this process, by effectively generating a flow diagnosis result (501), it is possible to accurately diagnose the state of the vibrating tube (11) of the Coriolis mass flowmeter (1) and perform simple correction related to the flow rate.

(6-6. Effect 6)
In the process according to the present embodiment described above, the occurrence of a fault in the Coriolis mass flowmeter (1), the time required for maintenance or equipment replacement, the operating time, or the integrated flow rate of the fluid are predicted based on the density calibration result (151), the density diagnosis result (201), the wall thickness/rigidity diagnosis result (301), or the flow rate diagnosis result (501), and generated as a timing prediction diagnosis result. Therefore, in this process, the condition of the vibrating tube (11) of the Coriolis mass flowmeter (1) can be accurately diagnosed, and the diagnosis result can be effectively utilized.

(6-7. Effect 7)
In the process according to the present embodiment described above, if the density calibration result (151), the density diagnosis result (201), the wall thickness stiffness diagnosis result (301), or the flow rate diagnosis result (501) exceeds a predetermined alarm value, an abnormality related to the vibrating tube (11) is notified. Therefore, in this process, the condition of the vibrating tube (11) of the Coriolis mass flowmeter (1) is accurately diagnosed, and the diagnosis result is effectively utilized to provide useful information.

〔system〕
The information including the processing procedures, control procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified.

In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure. In other words, all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

Furthermore, each processing function performed by each device may be realized, in whole or in part, by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware using wired logic.

[Hardware]
Next, a hardware configuration example of the diagnostic device (2) will be described. Note that other devices can also have a similar hardware configuration. FIG. 44 is a diagram for explaining a hardware configuration example. As shown in FIG. 44, the diagnostic device (2) has a communication device (2a), a hard disk drive (HDD) (2b), a memory (2c), and a processor (2d). In addition, each unit shown in FIG. 44 is connected to each other by a bus or the like.

The communication device (2a) is a network interface card or the like, and communicates with other servers. The HDD (2b) stores the programs and DB that operate the functions shown in FIG. 4.

The processor (2d) reads out a program that executes the same processes as the respective processing units shown in FIG. 4 from the HDD (2b) or the like and expands it in the memory (2c), thereby operating a process that executes the respective functions described in FIG. 4 or the like. For example, this process executes the same functions as the respective processing units possessed by the diagnostic device (2). Specifically, the processor (2d) reads out a program having the same functions as the density error diagnostic unit (61), the thickness stiffness diagnostic unit (70), the flow rate error diagnosis simple correction unit (80), the timing prediction diagnostic unit (90), and the like from the HDD (2b) or the like. Then, the processor (2d) executes a process that executes the same processes as the density error diagnostic unit (61), the thickness stiffness diagnostic unit (70), the flow rate error diagnosis simple correction unit (80), the timing prediction diagnostic unit (90), and the like.

In this way, the diagnostic device (2) operates as an information processing device that executes various processing methods by reading and executing a program. The diagnostic device (2) can also realize functions similar to those of the above-mentioned embodiment by reading the program from a recording medium using a media reading device and executing the read program. Note that the program in these other embodiments is not limited to being executed by the diagnostic device (2). For example, the present invention can be similarly applied to cases where another computer or server executes a program, or where these cooperate to execute a program.

This program can be distributed via a network such as the Internet. In addition, this program can be recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO (Magneto-Optical disk), or a DVD (Digital Versatile Disc), and can be executed by being read from the recording medium by a computer.

REFERENCE SIGNS LIST 1 Coriolis mass flowmeter 2 Diagnostic device 3 Calibration device 10 Detection unit 11 Vibrating tube 20 Conversion unit 21 Drive control unit 22 Mass flow rate calculation unit 23 Density calculation unit 30 Display operation unit 31 External device 40 Calibration control unit 41 Mass flow rate calibration unit 51 Density calibration unit 60 Diagnostic control unit 61 Density error diagnostic unit 70 Wall thickness/rigidity diagnostic unit 80 Flow rate error simple correction unit 90 Timing prediction diagnostic unit 200 Transmitting/receiving unit 300 Notification unit 1000 Diagnostic system

Claims (8)

a transceiver for acquiring a density calibration result related to the calibration of the density of a fluid generated by calibrating a Coriolis mass flowmeter that measures a flow rate and density of a fluid flowing through a vibrating tube based on a Coriolis force acting on the vibrating tube;
a density error diagnosis unit that generates a density diagnosis result regarding a density error of the fluid before and after the density calibration based on the density calibration result;
a thickness and stiffness diagnosis unit that performs calculations regarding at least one of the thickness and stiffness of the vibration tube based on the density calibration result or the density diagnosis result, and generates a thickness and stiffness diagnosis result regarding a change in the vibration tube;
a flow rate error diagnosis simple correction unit that performs a calculation regarding a flow rate of the fluid based on the wall thickness stiffness diagnosis result and generates a flow rate diagnosis result regarding a flow rate error of the fluid;
A diagnostic device comprising: The density error diagnosis unit includes:
Calculating the density error using an initial density measurement coefficient, a density measurement coefficient indicated by the density calibration result, and the density of the object to be measured;
The thickness and rigidity diagnosis unit includes:
Using the rate of change of the density measurement coefficient indicated by the density calibration result or the density diagnosis result and the design value of the vibration tube, a thickness and stiffness diagnosis result is generated, the thickness and stiffness diagnosis result including at least one result related to a thickness change, a stiffness change, corrosion, and adhesion of the vibration tube;
When the wall thickness rigidity diagnosis result is equal to or greater than a threshold value, an abnormality related to the vibration pipe is detected.
The diagnostic device of claim 1 . The thickness and rigidity diagnosis unit includes:
generating a thickness/rigidity diagnosis result including at least one of an inner diameter, a wall thickness, a wall thickness change, a wall thickness change rate, a rigidity change rate, a corrosion diagnosis, and an adhesion diagnosis of the vibration tube;
The diagnostic device of claim 2 . The flow rate error diagnosis simple correction unit includes:
generating the flow diagnostic result including at least one of a flow correction coefficient and a flow error using at least one of a stiffness change rate, a wall thickness change rate, and a density measurement coefficient change rate of the vibration pipe;
and performing update control of a flow rate correction coefficient used by the Coriolis mass flowmeter to measure the flow rate based on the flow rate correction coefficient.
The diagnostic device of claim 1 . a timing prediction and diagnosis unit that predicts the occurrence of a fault in the Coriolis mass flowmeter, the time required for maintenance or equipment replacement, the operating time, or the integrated flow rate of the fluid based on the density calibration result, the density diagnosis result, the wall thickness and stiffness diagnosis result, or the flow rate diagnosis result, and generates the result as a timing prediction and diagnosis result;
The diagnostic device of claim 1 further comprising: a notification unit that notifies an abnormality related to the vibration pipe when the density calibration result, the density diagnosis result, the wall thickness rigidity diagnosis result, or the flow rate diagnosis result exceeds a predetermined alarm value;
The diagnostic device of claim 5 further comprising: The computer
A density calibration result is obtained regarding calibration of the density of the fluid generated by calibrating a Coriolis mass flowmeter that measures a flow rate and density of the fluid flowing through a vibrating tube based on a Coriolis force acting on the vibrating tube;
generating a density diagnostic result regarding a density error of the fluid before and after the density calibration based on the density calibration result;
Calculating at least one of the thickness and stiffness of the vibration tube based on the density calibration result or the density diagnosis result to generate a thickness stiffness diagnosis result regarding the change of the vibration tube;
Executing a calculation related to a flow rate of the fluid based on the wall thickness stiffness diagnosis result, and generating a flow rate diagnosis result related to a flow rate error of the fluid.
A diagnostic method to perform the action. On the computer,
A density calibration result is obtained regarding calibration of the density of the fluid generated by calibrating a Coriolis mass flowmeter that measures a flow rate and density of the fluid flowing through a vibrating tube based on a Coriolis force acting on the vibrating tube;
generating a density diagnostic result regarding a density error of the fluid before and after the density calibration based on the density calibration result;
Calculating at least one of the thickness and stiffness of the vibration tube based on the density calibration result or the density diagnosis result to generate a thickness stiffness diagnosis result regarding the change of the vibration tube;
Executing a calculation related to a flow rate of the fluid based on the wall thickness stiffness diagnosis result, and generating a flow rate diagnosis result related to a flow rate error of the fluid.
A diagnostic program that performs the process.

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