JP7830899B2 - Method for monitoring the condition of machinery and equipment, condition monitoring system, condition monitoring device, wind power generation device, and program - Google Patents

Description

This invention relates to a method for monitoring the condition of a mechanical device, a condition monitoring system, a condition monitoring device, a wind power generation device, and a program.

Traditionally, mechanical devices such as wind turbines are equipped with rolling bearings. Monitoring the condition of these rolling bearings and implementing control measures accordingly helps prevent malfunctions and ensures more efficient operation. Information used for monitoring the condition of rolling bearings includes vibration, sound, and rotational speed.

Patent Document 1 describes a bearing deterioration diagnostic device that uses "rotation-tracking analysis" to analyze how the magnitude of a particular order component of vibration noise changes with increasing or decreasing rotational speed. Furthermore, Patent Document 1 describes defining a database that associates rotational speed with vibration values, and comparing this information with measured vibration values to determine the bearing's condition.

International Publication No. 2017/145222

For example, in wind turbines, intermittent changes in rotational speed can occur due to the influence of external wind. In particular, because wind turbines operate at relatively low rotational speeds, changes in rotational speed, i.e., angular velocity, can occur even during one rotation of the rolling bearing. When the rotational speed fluctuates, the vibration frequency of each part of the rolling bearing also fluctuates. Therefore, if condition monitoring is performed using data uniformly collected over one rotation of the rolling bearing, the accuracy will decrease due to these fluctuations. Furthermore, in cases where the rotational speed is relatively low, such as in wind turbines, analysis of low-frequency components is necessary. In this case, to acquire a sufficient number of data points, it is necessary to set a long data sampling time. The longer the sampling time, the higher the possibility of rotational speed fluctuations, and the more susceptible the system becomes to these fluctuations. As a result, proper condition monitoring of the rolling bearing becomes difficult.

In light of the above-mentioned problems, the present invention aims to accurately monitor the state of a mechanical device even when the rotational speed changes intermittently in an environment where the rotational speed of the mechanical device may change.

To solve the above problems, the present invention has the following configuration. That is, a method for monitoring the state of a mechanical device that performs rotational motion,
An acquisition step of acquiring vibration information or sound information during the rotational operation of the aforementioned machine at regular time intervals,
A conversion step is provided to convert the vibration information or sound information acquired in the acquisition step into a waveform that represents a state where the rotational motion is at a constant angular velocity.
A diagnostic step in which the state of the mechanical device is diagnosed using the vibration information or sound information converted in the above conversion step,
It has.

Furthermore, another embodiment of the present invention has the following configuration: a condition monitoring system that monitors the condition of a machine using a condition monitoring method,
The aforementioned status monitoring method is:
An acquisition step of acquiring vibration information or sound information during the rotational operation of the aforementioned machine at regular time intervals,
A conversion step is provided to convert the vibration information or sound information acquired in the acquisition step into a waveform that represents a state where the rotational motion is at a constant angular velocity.
A diagnostic step in which the state of the mechanical device is diagnosed using the vibration information or sound information converted in the above conversion step,
It has.

Furthermore, another embodiment of the present invention has the following configuration: namely, a condition monitoring device for a rotating mechanical device,
An acquisition means for acquiring vibration information or sound information during the rotational operation of the aforementioned mechanical device at regular time intervals,
A conversion means that converts vibration information or sound information acquired by the acquisition means into a waveform that represents a state where the rotational motion is at a constant angular velocity,
A diagnostic means for diagnosing the state of the mechanical device using vibration information or sound information converted by the conversion means,
It has.

Furthermore, another embodiment of the present invention has the following configuration: namely, a wind power generation device,
A condition monitoring device,
Rolling bearings and
Equipped with,
The aforementioned status monitoring device is
An acquisition means for acquiring vibration information or sound information during the rotational operation of the aforementioned mechanical device at regular time intervals,
A conversion means that converts vibration information or sound information acquired by the acquisition means into a waveform that represents a state where the rotational motion is at a constant angular velocity,
A diagnostic means for diagnosing the state of the mechanical device using vibration information or sound information converted by the conversion means,
It has.

Furthermore, another embodiment of the present invention has the following configuration: namely, a program,
On the computer,
A process for acquiring vibration information or sound information during the rotational operation of a machine or device at regular time intervals,
A conversion step is provided to convert the vibration information or sound information acquired in the acquisition step into a waveform that represents a state where the rotational motion is at a constant angular velocity.
A diagnostic step in which the state of the mechanical device is diagnosed using the vibration information or sound information converted in the above conversion step,
Make it run.

The present invention makes it possible to accurately monitor the state of a machine even when the rotational speed of the machine changes intermittently, in environments where the rotational speed of the machine may change.

A diagram illustrating the conversion of vibration data according to one embodiment of the present invention. A schematic diagram showing an example of the device configuration according to one embodiment of the present invention. A schematic diagram showing an example of a functional configuration according to one embodiment of the present invention. A diagram illustrating an example of waveform detection according to the present invention. A flowchart illustrating a state monitoring process according to one embodiment of the present invention. A figure showing an example of a formula for calculating the frequency of each part of a rolling bearing according to one embodiment of the present invention.

The embodiments for carrying out the present invention will be described below with reference to the drawings and other documents. Note that the embodiments described below are merely one example for illustrating the present invention and are not intended to be interpreted as limiting the present invention. Furthermore, not all configurations described in each embodiment are necessarily essential for solving the problem of the present invention. In addition, in each drawing, the same components are assigned the same reference numeral to indicate their correspondence.

<First Embodiment>
The following describes a first embodiment of the present invention. The method according to this embodiment can be applied to rolling bearings for wind power generation equipment, which will be described later, as well as bearings that operate at low rotational speeds below a certain level, bearings with large fluctuations in rotational speed, and the type of machinery to which it can be applied is not particularly limited.

[Conversion of vibration data]
First, the conversion of vibration data according to this embodiment will be explained. Figure 1 is a diagram illustrating the conversion of vibration data according to the present invention. Figure 1(a) shows an example of vibration data A obtained from a measurement target via a vibration sensor or the like. In Figure 1(a), the horizontal axis represents time [s] and the vertical axis represents amplitude. Actual bearing vibration data is data in which many different vibrations of different frequencies are superimposed, but here we will explain using an example in which vibration data A includes only two vibration data B and C. In the example shown in Figure 1(a), the angular velocity of the rolling bearing increases with the passage of time, and the rotational speed increases proportionally. As a result, of the two vibration data B and C, the frequency of vibration data C gradually increases with the passage of time, and the waveform of the entire vibration data A shown in Figure 1(a) also changes. In Figure 1(a), the envelope shown above the vibration data corresponds to the waveform showing the result of envelope processing. Note that the rotational speed is not limited to the fluctuations shown in Figure 1(a), and may change to decrease with the passage of time, or it may increase or decrease within a certain period.

Figure 1(b) shows the result of applying envelope processing and FFT (Fast Fourier Transform) processing to the waveform shown in Figure 1(a). In Figure 1(b), the horizontal axis represents frequency [Hz], and the vertical axis represents intensity. In this case, due to the fluctuation in rotational speed in vibration data C, the frequency peak cannot be detected, as shown in region 101 of Figure 1(b). Therefore, it is impossible to determine the frequency characteristics of vibration data C, making analysis based on frequency characteristics difficult.

As mentioned above, for example, frequency analysis is used for condition monitoring of rolling bearings in wind power generation equipment. The natural frequency of vibration in a rolling bearing is proportional to the angular velocity during rotation, and frequency analysis requires data from a state where the rolling bearing is rotating at a constant speed. Therefore, conventional methods assume a stable rotational speed and sample data at regular time intervals when detecting data for diagnostic purposes. However, if the angular velocity fluctuates during one rotation of the rolling bearing, causing the vibration frequency to change, the accuracy of condition monitoring decreases with the above method.

Therefore, in this embodiment, vibration data sampled at equal time intervals while exhibiting angular velocity fluctuations is converted into vibration data corresponding to a state where the angular velocity is constant, i.e., rotation at a constant speed.

Figure 1(c) shows an example of vibration data D obtained by applying the process to remove the effects of rotational speed fluctuations according to this embodiment to vibration data A shown in Figure 1(a). In Figure 1(c), the horizontal axis represents time [s], and the vertical axis represents amplitude. In Figure 1(c), vibration data A from Figure 1(a) is transformed to correspond to a state where the angular velocity is constant, i.e., constant-speed rotation.

In the conversion method according to this embodiment, first, _t0 that satisfies the following equation (1) is determined using the original vibration data and a predetermined angular velocity. Here, the predetermined angular velocity is described as the initial angular velocity _ω0 in the vibration data, but is not limited to this. For example, it may be the average value or the maximum value of the angular velocity within a predetermined range of the vibration data. It may also be the angular velocity at a predetermined timing of the vibration data.

Furthermore, the vibration data A before conversion and the vibration data D after conversion are converted using the following equation (2).

D(t ₁ )=A(t ₀ )...(2)
A(t): Vibration data before conversion at time t D(t): Vibration data after conversion at time t

The transformation using equations (1) and (2) above yields the vibration data D shown in Figure 1(c). In other words, vibration data D corresponds to waveform data when the angular velocity is constant (here, the initial angular velocity ω ₀ ). In Figure 1(c), the envelope shown above vibration data D corresponds to the waveform showing the result of envelope processing.

Figure 1(d) shows the result of applying envelope processing and FFT processing to the waveform shown in Figure 1(c). In Figure 1(d), the horizontal axis represents frequency [Hz], and the vertical axis represents intensity. Since the waveform assumes a constant rotational speed, frequency peaks can be detected, as shown in region 102 of Figure 1(d), enabling analysis based on its frequency characteristics.

The above example shows the process of performing data conversion, envelope processing, and FFT processing on vibration data in that order, but it is not limited to this. For example, the processes could be performed in the order of envelope processing, data conversion, and FFT processing. Alternatively, it may be possible to perform only data conversion and FFT processing without performing envelope processing.

Since the number of samples used to acquire vibration data A is finite, there may be cases where vibration data A( _t0 ) corresponding to time _t0 specified by equation (1) above does not exist in the vibration data A obtained by the vibration sensor or the like. In such cases, a predetermined range a may be set in advance, and vibration data D may be obtained using vibration data A( _t0 ') corresponding to _t0 ' which is included in the predetermined range with respect to _t0 , as shown in equation (3) below.

D(t ₁ )=A(t ₀ ') (t ₀ -a<t ₀ '<t ₀ +a)...(3)

Alternatively, an interpolation formula based on vibration data A(t) corresponding to t before and after _t0 (for convenience, let's call them _t0 -1 and _t0 +1) may be defined, as shown in equation (4) below, and vibration data D may be obtained.

D(t ₁ )={A(t ₀ -1)+A(t ₀ +1)}/2...(4)

The data interpolation method used during data conversion may be different from the methods described above, and the interpolation method may be switched depending on the purpose.

[Device configuration]
The following describes an embodiment of an apparatus to which the condition monitoring method of the present invention can be applied. In the following description, a wind power generation device including rolling bearings will be used as an example of application, but the method is not limited to wind power generation devices and can be similarly applied to other mechanical devices.

Figure 2 is a schematic diagram of a wind power generation device to which the load estimation method according to this embodiment is applied. As shown in Figure 2, the wind power generation device 10 comprises a tower 11 erected on the ground, a nacelle 12 supported at the upper end of the tower 11, and a rotor 13 provided at the end of the nacelle 12. A rotation mechanism 14 for adjusting the orientation (yaw control) of the nacelle 12 is provided between the tower 11 and the nacelle 12.

The nacelle 12 houses the drivetrain 21. The drivetrain 21 comprises a main shaft 22, a speed increaser 23, a generator 24, and rolling bearings 25. The main shaft 22 is connected to the generator 24 via the speed increaser 23. The main shaft 22 is rotatably supported within the nacelle 12 by the rolling bearings 25. Vibration sensors 27 are provided on the rolling bearings 25 and the speed increaser 23 to measure vibrations generated in the rolling bearings 25. A rotational speed sensor 26 is also provided to detect the rotational speed of the main shaft 22. The generator 24 is equipped with a power generation measuring device (not shown) for measuring the amount of power generated.

The rotor 13 has a hub 16 and multiple blades 15. Each of the multiple blades 15 extends radially from the hub 16. The rotor 13 is provided at the end of the main shaft 22 of the drivetrain section 21. The hub 16 adjusts (controls the pitch) the orientation of each of the multiple blades 15.

Furthermore, in the wind power generation device 10, the rotating shafts of the speed increaser 23 and the generator 24 are also supported by rolling bearings (not shown) that are separate from the rolling bearings 25. Rotational speed sensors 26 are provided on both the rolling bearing 25 side of the speed increaser 23 and the generator 24 side to detect the rotational speed of the rotating shafts. Vibration sensors 27 are also provided on the rolling bearings 25 and the generator 24. Additionally, the drivetrain section 21 is equipped with a braking device (not shown) to stop or decelerate the rotation of the main shaft 22 as needed.

In the wind power generation device 10 with the above structure, the main shaft 22 rotates when the blades 15 of the rotor 13 receive wind. This rotation of the main shaft 22 is then accelerated by the speed increaser 23 and transmitted to the generator 24, which generates electricity. Furthermore, the wind received by the blades 15 of the rotor 13 imparts a load (radial load and axial load) to the rolling bearing 25 via the main shaft 22. Note that Figure 2 shows a configuration with one rolling bearing 25 for one wind power generation device 10 for simplification of the explanation; however, the configuration is not limited to this, and multiple rolling bearings 25 may be provided to support the main shaft 22 in one wind power generation device 10.

[Functional Configuration]
Figure 3 is a schematic diagram showing an example of the functional configuration according to this embodiment. Figure 3 shows the configuration of the rolling bearing 25 to be monitored and the monitoring device 50 that performs the monitoring operation according to this embodiment. The rolling bearing 25 rotatably supports the main shaft 22. In this embodiment, the rolling bearing 25 can be, for example, a tapered roller bearing, a cylindrical roller bearing, etc., but is not limited to these.

The monitoring device 50 may be installed inside the wind power generation device 10 shown in Figure 2, or it may be installed outside the wind power generation device 10. Furthermore, Figure 3 shows a configuration in which one monitoring device 50 monitors one rolling bearing 25 for the sake of simplicity. However, the configuration is not limited to this, and the one monitoring device 50 may be configured to monitor the condition of multiple rolling bearings 25.

The rolling bearing 25 comprises an inner ring 40, which is a rotating ring fitted onto the main shaft 22; an outer ring 42, which is a stationary ring fitted into a housing (not shown); a plurality of rolling elements 41, which are multiple balls (rollers), arranged between the inner ring 40 and the outer ring 42; and a cage 43 that holds the rolling elements 41 so that they can roll freely. Furthermore, in the rolling bearing 25, friction between the inner ring 40 and the rolling elements 41, and between the outer ring 42 and the rolling elements 41, is reduced by a predetermined lubrication method. The lubrication method is not particularly limited, but for example, grease lubrication or oil lubrication can be used. The type of lubricant is also not particularly limited.

A vibration sensor 27 is provided to detect vibrations generated from the rolling bearing 25 during the rotation of the main shaft 22. The vibration sensor 27 is fixed near the outer ring of the housing by means of bolt fixing, adhesive, bolt fixing and adhesive, or embedding with molded material. In the case of bolt fixing, a rotation prevention function may be provided. Note that the vibration sensor 27 is not limited to being fixed in a detection position; it only needs to be installed in a position to detect vibrations from the rolling bearing 25 during condition monitoring. Therefore, the vibration sensor 27 may be detachable or movable.

Furthermore, the vibration sensor 27 can be any device capable of detecting vibration, such as an acceleration sensor, AE (Acoustic Emission) sensor, ultrasonic sensor, or shock pulse sensor, as long as it can convert the detected vibration (acceleration, velocity, strain, stress, displacement, etc.) into an electrical signal. When installing it in a wind power generation device 10 located in a noisy environment, using an insulated type is preferable as it is less affected by noise. Additionally, if the vibration sensor 27 uses a vibration detection element such as a piezoelectric element, this element may be molded in plastic or the like.

Furthermore, the rolling bearing 25 is equipped with a rotational speed sensor 26 that detects the rotational speed of the inner ring 40 fitted onto the main shaft 22. In this embodiment, the rotational speed and rotational frequency of the inner ring 40, which is a rotating ring, and the main shaft 22 are the same. The rotational speed of the main shaft 22 may fluctuate depending on the direction, volume, and pressure of the wind acting on the wind power generation device 10. Furthermore, the rotational speed can be adjusted by a braking device (not shown). The rotational speed sensor 26 may detect the rotational speed by, for example, detecting an encoder (not shown) provided on the inner ring 40 of the rolling bearing 25. The wind power generation device 10 according to this embodiment rotates at a relatively low rotational speed. Therefore, the rotational speed sensor 26 is configured to detect changes in rotational speed during one rotation of the rolling bearing 25. Note that the vibration sensor 27 and the rotational speed sensor 26 may be configured to perform detection operations only at specified timings (e.g., monitoring time periods), or they may be configured to perform detection operations continuously.

The amplifier 44 amplifies the electrical signal detected by the vibration sensor 27 and inputs it to the monitoring device 50. The degree of amplification is not particularly limited, but is predetermined. The detection timings of the vibration sensor 27 and the rotational speed sensor 26 correspond, and their detection information is processed in correspondence.

The monitoring device 50 may be implemented as an information processing device comprising, for example, a control device, a storage device, and an input/output device (not shown). The control device may consist of a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a DSP (Digital Single Processor), or a dedicated circuit. The storage device consists of volatile and non-volatile storage media such as an HDD (Hard Disk Drive), ROM (Read Only Memory), or RAM (Random Access Memory), and is capable of inputting and outputting various types of information in response to instructions from the control device. The input/output device notifies external devices or operators in response to instructions from the control device. The output method by the input/output device is not particularly limited, but for example, it may be an auditory notification by voice, or a visual notification by screen output. Furthermore, the input/output device may be a network interface equipped with communication functions, and various input/output operations may be performed by sending and receiving data with an external device (not shown) via a network (not shown).

The monitoring device 50 includes an A/D conversion unit 51, a data conversion unit 52, a vibration signal processing unit 53, and a monitoring processing unit 54. Each component may be implemented by the control device described above reading and executing the corresponding program from a storage device. Furthermore, the control device may implement various functions by controlling input/output devices.

The A/D conversion unit 51 acquires the electrical signal detected by the vibration sensor 27 as vibration information via the amplifier 44, and performs A/D (Analog/Digital) conversion according to the content of the electrical signal.

The data conversion unit 52 performs a conversion process based on the rotational speed detected by the rotational speed sensor 26, using the data from the vibration signal processed by the A/D conversion unit 51 for processing in the subsequent vibration signal processing unit 53 and monitoring processing unit 54. The conversion process here is performed using the method described with reference to Figure 1. The converted data is output to the vibration signal processing unit 53.

The vibration signal processing unit 53 performs signal analysis processing using the data output from the data conversion unit 52. In the signal analysis processing, Fast Fourier Transform (FFT) analysis is performed, followed by order ratio analysis. Envelope processing, or filtering using low-pass or band-pass filters, may also be performed before signal analysis. As described above, the order of data conversion processing, envelope processing, and FFT processing according to this embodiment can be varied depending on the purpose; therefore, the data conversion unit 52 and the vibration signal processing unit 53 may cooperate to control the processing order.

The monitoring processing unit 54 uses the data processed by the vibration signal processing unit 53 to diagnose the condition of the rolling bearing 25 and outputs the diagnosis result. For example, a portion of the data processed by the vibration signal processing unit 53 may be extracted and used to diagnose the condition. The diagnostic items for condition monitoring performed by the monitoring processing unit 54 are not particularly limited, but any diagnostic items may be targeted, such as rotational slip, orbital slip, abnormal contact, poor lubrication, damage or deterioration of the various parts constituting the rolling bearing 25.

The monitoring results from the monitoring processing unit 54 may be reported externally via a network (not shown), or the operation of the wind turbine 10 may be controlled. For example, the operation of the wind turbine 10 may be controlled by adjusting the orientation of the nacelle 12 (yaw control) by controlling the rotation mechanism 14, or by adjusting the orientation of each of the multiple blades 15 (pitch control) by controlling the hub 16. Furthermore, a brake mechanism (not shown) may be used to control the rotational speed of the main shaft 22 to a predetermined speed.

[Data conversion process]
The following describes the data conversion process using a wind power generation device 10 to which the state monitoring method according to this embodiment can be applied as an example.

Figure 4 shows an example of rotational speed information of the rolling bearing 25 of the wind power generation device 10 obtained by the rotational speed sensor 26. In Figure 4(a), the horizontal axis represents time [s], and the vertical axis represents the output value of the rotational speed sensor 26. For example, when the rotational speed sensor 26 detects a predetermined marker (not shown) provided on the rolling bearing 25, a peak value as shown in Figure 4(a) is output. The configuration of the marker is not particularly limited, but for example, it may be provided so that it is detected once for each rotation of the rolling bearing 25.

Figure 4(b) shows an example of deriving frequency by performing FFT processing on the signal shown in Figure 4(a). In Figure 4(b), the horizontal axis represents frequency [Hz], and the vertical axis represents intensity. Angular velocity can be derived based on the detection timing of the peak value shown in the signal in Figure 4(b).

The above example shows the process of performing rotational speed conversion, envelope processing, and FFT processing on vibration data in that order, but it is not limited to this. For example, the processes could be performed in the order of envelope processing, rotational speed conversion, and FFT processing.

[Processing Flow]
Figure 5 is a flowchart of the sampling process according to this embodiment. This process is performed by the monitoring device 50, and may be implemented, for example, by the control device (not shown) of the monitoring device 50 reading a program for implementing each part shown in Figure 3 from a storage device (not shown) and executing it.

In step S501, the monitoring device 50 acquires vibration data detected by the vibration sensor 27 and rotational speed detected by the rotational speed sensor 26. The vibration data and rotational speed acquired here are associated with the detection timing.

In S502, the monitoring device 50 converts the vibration data acquired in S501 based on the rotational speed acquired in S501. Here, assuming that the angular velocity of the rolling bearing 25 is fluctuating, the vibration data is converted using equations (1) and (2) above, assuming it is rotating at a constant angular velocity. As explained using Figure 4, the monitoring device 50 can derive the angular velocity of the rolling bearing 25 from the rotational speed, and this angular velocity can be used in the data conversion process.

In S503, the monitoring device 50 performs signal analysis on the data converted in S503. This analysis may involve, for example, FFT analysis of vibration information followed by order ratio analysis. As described above, envelope analysis or filtering may be applied to the sampled data, and the content of these processes may be modified according to the subsequent monitoring process.

In S504, the monitoring device 50 monitors the condition of the rolling bearing 25 using the results of the analysis processing in S504. The monitoring items here are not particularly limited, but may include any diagnostic items such as rotational slip, orthogonal slip of the rolling bearing 25, or abnormal contact, poor lubrication, damage, or deterioration of the various parts constituting the rolling bearing 25. Furthermore, regarding the monitoring items, for example, the frequency of each part of the rolling bearing 25 may be calculated using the relational formula shown in Figure 6, and the presence or absence of rotational slip or orthogonal slip may be determined by the difference between that frequency and the peak frequency thought to be generated by that part. Alternatively, the presence or absence of an abnormality may be determined by comparing the peak value of the analysis result with a predetermined threshold.

In S505, the monitoring device 50 performs notification processing based on the results of the status monitoring process in S504. Here, notification may be issued if an abnormality is detected, or it may be configured to issue a notification even if no abnormality is detected. Furthermore, the notification method is not particularly limited, and the notification method may be switched depending on whether or not an abnormality is detected. Then, this processing flow ends.

In summary, this embodiment makes it possible to accurately monitor the state of a machine even when the rotational speed of the machine changes intermittently, in environments where the rotational speed of the machine may change.

<Other Embodiments>
In the above embodiment, a configuration was shown in which vibration of the rolling bearing 25 is detected using a vibration sensor 27, but the invention is not limited to this. Instead of the vibration sensor 27, a sound sensor including a microphone may be used to detect sound data. In this case, the above-described data conversion processing is performed on the sound data. Therefore, the present invention can perform processing using waveform data such as vibration data and sound data.

Furthermore, the present invention can also be realized by supplying a program or application for realizing the functions of one or more embodiments described above to a system or device using a network or storage medium, and having one or more processors in the computer of that system or device read and execute the program.

Furthermore, these functions may be implemented using circuits that perform one or more functions (for example, ASICs (Application Specific Integrated Circuits) or FPGAs (Field Programmable Gate Arrays)).

Thus, the present invention is not limited to the embodiments described above. Combining the various components of the embodiments, modifying and applying them based on the description in this specification and well-known technology, is also intended by those skilled in the art and falls within the scope of protection.

As described above, the following matters are disclosed in this specification:
(1) A method for monitoring the condition of a machine device that performs rotational motion (for example, 10),
An acquisition step (for example, S501) for acquiring vibration information or sound information during the rotational operation of the aforementioned machine device at regular time intervals,
A conversion step (for example, S502) is performed to convert the vibration information or sound information acquired in the acquisition step into a waveform that represents a state where the rotational motion is at a constant angular velocity.
A diagnostic step (for example, S503, S504) for diagnosing the state of the machine using the vibration information or sound information converted in the conversion step,
A condition monitoring method characterized by having the following features.
This configuration allows for accurate monitoring of the state of a machine even in environments where the rotational speed of the machine may change intermittently, even when changes in rotational speed occur.

(2) The state monitoring method according to (1), characterized in that the conversion step converts the angular velocity at a predetermined timing when vibration information or sound information is acquired in the acquisition step as the constant angular velocity.
With this configuration, for example, vibration data can be converted into a waveform with a constant angular velocity based on the initial angular velocity of the vibration data, making it possible to perform condition monitoring with high accuracy.

(3) The conversion process is as follows:

The state monitoring method according to (1) or (2), characterized in that it performs a conversion using
This configuration makes it possible to convert vibration data using relatively simple calculations.

(4) The method further includes a derivation step (for example, S501, S502) for deriving the angular velocity during rotational operation based on the rotational speed of the machine device during said rotational operation,
The conversion step converts the vibration information or sound information acquired in the acquisition step based on the angular velocity derived in the derivation step.
A condition monitoring method according to any one of (1) to (3), characterized by the above.
This configuration makes it possible to appropriately derive the angular velocity in the rotational motion of a mechanical device and use it for data conversion.

(5) The status monitoring method according to any one of (1) to (4), characterized in that the conversion step is performed using the information acquired in the acquisition step, or the information obtained by applying envelope processing to the information acquired in the acquisition step.
With this configuration, data conversion processing can be applied to either raw vibration data or envelope-processed vibration data, making it possible to use different types of vibration data for data conversion depending on the purpose.

(6) The condition monitoring method according to any one of (1) to (5), characterized in that the machine device is a bearing device (for example, 23).
This configuration makes it possible to accurately monitor the condition of bearing devices.

(7) The condition monitoring method according to any one of (1) to (5), characterized in that the machine is a wind power generation device (for example, 10) equipped with rolling bearings (for example, 25).
This configuration makes it possible to accurately monitor the condition of wind power generation equipment.

(8) A condition monitoring system (e.g., 50) that monitors the condition of a machine (e.g., 10) using the condition monitoring method described in any of (1) to (7).
This configuration makes it possible to provide a condition monitoring system that can accurately monitor the condition of machinery and equipment.

(9) A condition monitoring device (e.g., 50) for a rotating mechanical device (e.g., 10),
Acquisition means (for example, 44, 51) for acquiring vibration information or sound information during the rotational operation of the aforementioned machine device at regular time intervals,
A conversion means (for example, 52, 53) converts the vibration information or sound information acquired by the acquisition means into a waveform that represents a state where the rotational motion is at a constant angular velocity,
A diagnostic means (for example, 54) that diagnoses the state of the mechanical device using vibration information or sound information converted by the conversion means,
A condition monitoring device characterized by having the following features.
This configuration makes it possible to accurately monitor the state of a machine even when the rotational speed of the machine changes intermittently, in environments where the rotational speed of the machine may change.

(10) The condition monitoring device described in (9) (for example, 50),
A rolling bearing (for example, 25) and
A wind power generation device (for example, 10) equipped with the following.
This configuration makes it possible to accurately monitor the condition of a wind power generation device even when its rotational speed changes during operation.

(11) A computer (for example, 50)
An acquisition step (for example, S601) is performed to acquire vibration information or sound information during the rotational operation of a machine or device at regular time intervals,
A conversion step (for example, S502) is performed to convert the vibration information or sound information acquired in the acquisition step into a waveform that represents a state where the rotational motion is at a constant angular velocity.
A diagnostic step (for example, S503, S504) for diagnosing the state of the machine using the vibration information or sound information converted in the conversion step,
A program to execute.
This configuration allows the computer to be controlled in a way that enables accurate monitoring of the state of the mechanical device even when the rotational speed of the device changes intermittently, in environments where the rotational speed of the mechanical device may change.

10...Wind turbine 11...Tower 12...Nacelle 13...Rotor 14...Rotating mechanism 15...Blade 16...Hub 21...Drivetrain section 22...Main shaft 23...Speed increaser 24...Generator 25...Rolling bearing 26...Rotation speed sensor 27...Vibration sensor 40...Inner ring 41...Rolling element 42...Outer ring 43...Cage 44...Amplifier 50...Monitoring device 51...A/D conversion unit 52...Data conversion unit 53...Vibration signal processing unit 54...Monitoring processing unit

Claims (9)

A method for monitoring the condition of a rotating mechanical device,
An acquisition step of acquiring vibration information or sound information during the rotational operation of the aforementioned machine at regular time intervals,
A conversion step is provided to convert the vibration information or sound information acquired in the acquisition step into a waveform that represents a state where the rotational motion is at a constant angular velocity.
A diagnostic step in which the state of the mechanical device is diagnosed using the vibration information or sound information converted in the above conversion step,
The process includes a derivation step of deriving the angular velocity during rotational operation based on the rotational speed of the aforementioned mechanical device during the rotational operation ,
The aforementioned conversion process is
Using,
A condition monitoring method characterized by converting vibration information or sound information acquired in the acquisition step based on the angular velocity derived in the derivation step . The state monitoring method according to claim 1, characterized in that the conversion step converts the angular velocity at a predetermined timing when vibration information or sound information is acquired in the acquisition step into the constant angular velocity. The status monitoring method according to either claim 1 or 2, characterized in that the conversion step is performed using information acquired in the acquisition step, or information obtained by applying envelope processing to the information acquired in the acquisition step. The condition monitoring method according to any one of claims 1 to 3 , characterized in that the aforementioned mechanical device is a bearing device. The condition monitoring method according to any one of claims 1 to 3 , characterized in that the aforementioned mechanical device is a wind power generation device equipped with rolling bearings. A condition monitoring system that monitors the condition of a machine or device using the condition monitoring method described in any one of claims 1 to 5 . A device for monitoring the condition of a rotating mechanical device,
An acquisition means for acquiring vibration information or sound information during the rotational operation of the aforementioned mechanical device at regular time intervals,
A conversion means that converts vibration information or sound information acquired by the acquisition means into a waveform that represents a state where the rotational motion is at a constant angular velocity,
A diagnostic means for diagnosing the state of the mechanical device using vibration information or sound information converted by the conversion means,
The device includes a derivation means for deriving the angular velocity during rotational operation based on the rotational speed during the rotational operation of the aforementioned mechanical device ,
The conversion means is
Using,
A condition monitoring device characterized by converting vibration information or sound information acquired by the acquisition means based on the angular velocity derived by the derivation means . A condition monitoring device according to claim 7 ,
Rolling bearings and
A wind power generation device equipped with the following features. On the computer,
A process for acquiring vibration information or sound information during the rotational operation of a machine or device at regular time intervals,
A conversion step is provided to convert the vibration information or sound information acquired in the acquisition step into a waveform that represents a state where the rotational motion is at a constant angular velocity.
A diagnostic step in which the state of the mechanical device is diagnosed using the vibration information or sound information converted in the above conversion step,
A derivation step is performed to derive the angular velocity during the rotational operation of the aforementioned machine device based on the rotational speed during the said rotational operation .
The aforementioned conversion process is,
Using,
A program for performing a conversion of vibration information or sound information acquired in the acquisition step, based on the angular velocity derived in the derivation step .