JP7655873B2 - Equipment Deterioration Monitoring System - Google Patents

Description

The present invention relates to a facility deterioration monitoring system using a data reconciliation technique.

The equipment and instruments used in power plants deteriorate over time. For example, valve seat leaks can occur, the heat transfer performance of a heat exchanger can decrease due to fouling of the heat transfer tubes, and rust can build up on the surface of a flow meter's flow nozzle, causing the flow meter's reading to drift. Such deterioration of plant equipment and devices can reduce the power generation efficiency of thermal and nuclear power plants.

When a decrease in power generation efficiency occurs during operation, it is necessary to determine from parameters during plant operation whether the cause is deterioration of the plant facilities and instruments due to a steam leak, deterioration of the equipment, or instrument drift. Identifying the cause of the decrease in power generation efficiency and carrying out appropriate maintenance is important for maintaining high power generation efficiency in thermal and nuclear power plants.

For this reason, various techniques have been devised to identify the causes of deterioration of plant equipment and instruments. For example, in Patent Document 1, a unique true value estimation model is used to estimate true values based on the actual measured values of each detector signal of the plant. Then, by using an estimated true value integration means that performs a comprehensive evaluation of each estimated true value from data related to accuracy, and a data reconciliation technique that is a consistency improvement means that calculates an estimated true value that is consistent as a system, the most likely estimated true value is found, and an estimated drift amount of the instrument can be calculated to identify the causes of performance deterioration, and it is also shown that aging and performance deterioration of the equipment can be evaluated.

By using data reconciliation technology, it is possible to perform more efficient and reliable analysis compared to estimating the deterioration of plant equipment and instruments using only measurement data during plant operation. This enables proper monitoring and maintenance of plant equipment and instruments, and helps prevent power generation losses at the plant.

JP 2005-338049 A

The technology in Patent Document 1 makes it possible to evaluate equipment aging and performance degradation based on the actual measured values of each detector signal in a plant. However, there are problems that make it impossible to apply the technology in Patent Document 1, such as the fact that a method for detecting valve seat leaks that result in power generation loss based on the actual measured values of detector signals has not been established, that a baseline method for performing high-precision data reconciliation evaluation has not been established, and that data reconciliation evaluation cannot be performed if there is no redundancy in the detector.

An object of the present invention is to solve the above problems and provide a highly accurate facility deterioration monitoring system having a wide range of applications.

In order to achieve the above object, an equipment deterioration monitoring system equipped with a plant instrumentation device for determining the state of plant equipment or instruments used in a power generation plant includes a measurement value input unit for inputting actual measurement values of instruments installed in the plant as measurement values of measurement variables, a virtual variable setting unit for setting measurement information of a virtual instrument virtually installed in the plant as a virtual variable, a constraint condition setting unit for setting constraint conditions related to the measurement variables or the virtual variables, and a true value estimation unit for calculating estimated true values of the measurement variables and the virtual variables from the measurement variables, the virtual variables, and the constraint conditions by a least squares method using the uncertainty of the measurement variables as a weight so that the deviation between the measurement values of the measurement variables and the virtual variables is minimized, and the virtual variables are set as assumed deterioration variables indicating the deterioration state of equipment at assumed locations of the plant equipment, and the system is equipped with an equipment deterioration determination device for determining whether the estimated true value of the assumed deterioration variable calculated by the plant instrumentation device is equal to or greater than a threshold value, and determining that deterioration has occurred in the equipment corresponding to the assumed deterioration variable if the estimated true value is equal to or greater than the threshold value.

According to the present invention, it is possible to provide a highly accurate facility deterioration monitoring system with a wide range of applications.

FIG. 1 is a diagram showing a specific example before the application of DR technology. FIG. 13 is a diagram showing a specific example after application of DR technology. FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. 1 is a schematic diagram of a secondary cooling system of a nuclear reactor plant. FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. FIG. 2 is a diagram illustrating the operation of the plant maintenance optimization system. FIG. 1 is a configuration diagram of a plant maintenance optimization system equipped with a plant instrumentation device.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
First, a data reconciliation technique (hereinafter referred to as DR technique) used in the plant instrumentation device of the embodiment will be described.

DR technology is a true value estimation method that reduces the uncertainty of instruments by using information from existing sensors that are redundant, i.e., multiple sensors that are installed to detect the same parameters, and estimates highly reliable true values by satisfying conservation laws between instruments.

In more detail, DR technology calculates the estimated true value yi of the best process that is the solution to the two simultaneous equations in Equation 1 using the least squares method, weighted by the uncertainty of the measurement value, so that the deviation between the measurement value xi and the estimated true value yi is minimized, where i is each instrument in the plant, xi is the measurement value (actual value) of each instrument, yi is the estimated true value, σi is the uncertainty of each measurement value, J(yi) is the objective function, and f(yi) is the constraint.

Figures 1A and 1B show specific examples before and after the application of DR technology. Note that (t/h) in Figures 1A and 1B indicates mass flow rate (tons/hour).

As shown in Figure 1A, the flow rate measurement values of meters A, B, and C before the application of DR technology do not match at the inlet and outlet of the container. This occurs because each meter has a measurement error when there is no leakage from the container.

By applying DR technology based on the instrument errors and measurement values xi of meters A, B, and C in Figure 1A, it is possible to obtain the estimated true value yi of the flow rate at the installation locations of meters A, B, and C, and the estimated error range σi (uncertainty). As shown in Figure 1B, the estimated true value yi of the flow rate is consistent at the inlet and outlet sides of the container, and the measurement errors of each meter A, B, and C are also reduced.

The plant instrumentation device of the embodiment focuses on the principle that DR technology can calculate the estimated true value yi of an instrument by using instrument redundancy, i.e., information from multiple previously designed instruments installed to detect the same parameter, and satisfying the conservation laws between the instruments. Undetectable information such as steam leaks or measurement values related to expected deterioration of the plant are incorporated into the DR technology as virtual variables, and the conservation laws or balance laws of the virtual variables are incorporated into the DR technology as constraints to estimate the true value.

In addition, the plant instrumentation device of the embodiment uses the output of the plant heat balance calculation as the measurement value of the virtual variables of the DR technology, and serves as a baseline for high-precision evaluation.

Furthermore, the plant instrumentation device of the embodiment applies, as constraint conditions to the DR technology, statistical models such as pressure characteristics inside the turbine of the plant, pressure balance calculations of pressure losses in piping and equipment, and models incorporating relationships between instruments determined based on past normal operating data, and internal calculation formulas of a simulator that simulates plant behavior, or applies the outputs of these to the DR technology as measurement values xi, thereby increasing redundancy and improving the application range of the DR technology.
Hereinafter, the configuration of the plant instrumentation device of the embodiment will be described in more detail.

Figure 2 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device 1 according to an embodiment.

The equipment deterioration monitoring system in Figure 2 is applied to the operation management of thermal and nuclear power plants, and applies measurement variables based on the instrument signals within the plant, valve seat leakage amount, heat exchanger tube leakage amount, heat exchanger heat transfer performance degradation amount, heat exchanger tube leakage amount, pump performance degradation amount, etc. to DR technology as hypothetical variables (hereinafter referred to as assumed deterioration variables), and judges the equipment deterioration of the plant equipment based on the values of the assumed deterioration variables estimated by DR technology.

Here, the assumed degradation variables (virtual variables) in the first embodiment will be described in more detail.
The assumed deterioration variables are measured values using virtual instruments in a plant where no actual instruments are installed, and are virtual variables of the DR technology that assume the deterioration state of the equipment. For example, the amount of valve seat leakage at each location in a power plant, the amount of deterioration in the heat transfer performance of a heat exchanger, the amount of heat exchanger tube leakage, the amount of reduction in pump head, etc. are quantitative virtual variables corresponding to the assumed type of deterioration of the plant equipment.

In addition to the actual measured values of each instrument in the plant, the plant instrumentation device 1 sets expected degradation variables as measured values of virtual instruments at locations in the plant where degradation is expected to occur, and applies DR technology to estimate the true value of the expected degradation variables. The equipment degradation judgment device 31 then judges the degradation of equipment and facilities from the fluctuation of the expected degradation variables estimated by the plant instrumentation device 1. The plant instrumentation device 1 may also use the drift amount of the instrument as the expected degradation variable. Furthermore, in the case of the heat transfer performance of a heater, the decrease in the outlet temperature of the non-heated side fluid or the increase in the drain temperature of the heated side fluid may be used as a quantitative expected degradation variable.

A specific example will be explained using the schematic diagram of the secondary cooling system of a nuclear reactor plant in Figure 3. In the secondary cooling system of Figure 3, the amount of steam leakage in the steam flow path from the reactor to the turbine is defined as the assumed degradation variable X1, the flow rate corresponding to the reduction in the head of the feedwater pump for cooling water condensed in the condenser is defined as the assumed degradation variable X2, and the flow rate corresponding to the reduction in the heat transfer performance of the heat exchanger is defined as the assumed degradation variable X3.

When the assumed degradation variables X1, X2, and X3 are in a healthy state, and DR technology is applied to the overall conservation calculation, the assumed degradation variables X1 = 0, X2 = 0, and X3 = 0 (t/h). If the assumed degradation variables X1 = 20, X2 = 0, and X3 = 0 (t/h) result when the amount of power generation decreases, it can be estimated that a steam leak of 20 (t/h) has occurred in the flow path from the reactor to the turbine, where assumed degradation variable X1 is set, causing the decrease in power generation.

Returning to FIG. 2, the configuration of the facility deterioration monitoring system will be described.
The equipment deterioration monitoring system comprises a plant instrumentation device 1 that calculates an assumed deterioration variable based on information from plant instruments, and an equipment deterioration determination device 31 that determines the deterioration of equipment from the assumed deterioration variable.

The plant instrumentation device 1 is composed of a measurement value input section 21, a virtual variable setting section 22, a constraint condition setting section 23, and a true value estimation section 10.

The measurement value input unit 21 acquires the actual measurement values of each instrument in the plant and notifies the true value estimation unit 10 of the measurement values of the measurement variables.

The virtual variable setting unit 22 sets virtual variables (assumed degradation variables) to be incorporated into the true value estimation unit 10.

The constraint condition setting unit 23 sets the conservation law or balance law of variables (measured variables and virtual variables) as constraint conditions in DR technology when the true value estimation unit 10 calculates the estimated true value.

The true value estimation unit 10 is composed of a storage unit for information on measurement variables 11, virtual variables 12, and constraint conditions 13, and a DR processing unit 14.

The measurement variables 11 store the actual measured values of each instrument in the plant notified by the measurement value input unit 21 as measured values for processing in the DR processing unit 14, and also indicate the estimated true values calculated by the DR processing unit 14.

The virtual variable 12 is set by the virtual variable setting unit 22, stores the virtual measurement value of the virtual variable in the DR processing unit 14, and indicates the estimated true value calculated by the DR processing unit 14.

Constraint conditions 13 stores the constraint conditions for DR technology set by the constraint condition setting unit 23.

The DR processing unit 14 is a processing unit that calculates the estimated true values yi of the measurement variables 11 and the virtual variables 12 according to the above formula 1. The DR processing unit 14 sets the accuracy of each instrument in the plant as the uncertainty σi.

Specifically, the plant instrumentation device 1 is configured by a computer consisting of a CPU that performs calculation processing, a memory, a communication unit, an operation unit, a display unit, and a non-volatile storage medium, and functions as a DR processing unit 14, a measurement value input unit 21, a virtual variable setting unit 22, and a constraint condition setting unit 23 by the CPU executing a program stored in the non-volatile storage medium. The measurement variables 11, virtual variables 12, and constraint conditions 13 are configured in the memory.

The equipment deterioration judgment device 31 judges whether the assumed deterioration variables X1, X2, and X3 calculated as estimated true values of virtual variables in the plant instrumentation device 1 are equal to or greater than a predetermined threshold. If the assumed deterioration variables X1, X2, and X3 are equal to or greater than the threshold, it is judged that deterioration has occurred in the equipment at the assumed location.

As a result, the equipment deterioration monitoring system of the embodiment can grasp the deterioration of locations where instruments are not actually installed by using the assumed deterioration variables estimated by the plant instrumentation device 1.

Next, we will explain the configuration of an embodiment of an equipment deterioration monitoring system that detects and determines both equipment deterioration and instrument drift.

FIG. 4 is a system configuration diagram of an equipment deterioration monitoring system including the plant instrumentation device 1 of the embodiment.
The plant instrumentation device 1 in Fig. 4 differs from the plant instrumentation device 1 in Fig. 2 in that it includes a penalty value calculation unit 15. The other configurations are the same as those in Fig. 2, and therefore will not be described here.

The penalty value calculation unit 15 calculates a penalty value defined by Equation 2 for each instrument in the plant from the measurement value (actual measurement value xi) of the instrument acquired by the measurement value input unit 21 and the estimated true value yi of the measurement value of the instrument estimated by the DR processing unit 14. Here, the uncertainty σi is determined from the instrument accuracy or the variation of the actual measurement value.
Penalty value = {(yi - xi)/σi}^2 ... Equation 2

The penalty value indicates the degree of deviation between the instrument's measurement (actual value) and the estimated true value. Therefore, even if the power generation or the equipment around the target instrument is healthy, if the penalty value becomes large, that is, the deviation of the target instrument's actual measurement value from the likely estimated true value becomes large, this indicates a high possibility that instrument drift is occurring.

The equipment deterioration/instrument drift determination device 32 detects and determines equipment deterioration when the assumed deterioration variable of the plant instrumentation device 1 changes, and detects and determines instrument drift when the penalty value fluctuates.
This enables the equipment deterioration monitoring system to grasp the deterioration state of the plant in detail.

Next, the configuration of the plant instrumentation device 1 that improves the accuracy of the estimated true value yi will be described.
FIG. 5 is a configuration diagram of an equipment deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

The plant instrumentation device 1 in FIG. 5 is configured by adding a plant heat balance calculation unit 24 to the plant instrumentation device 1 described in FIG. 2. The rest of the configuration is the same as in FIG. 2, so the description is omitted here. Note that the plant instrumentation device 1 in FIG. 4 may also be configured by adding a plant heat balance calculation unit 24.

The plant instrumentation device 1 is provided with a plant heat balance calculation unit 24 that uses the enthalpy at each location where no instruments are installed, the flow rate of the turbine extraction pipe, etc. as virtual variables and performs analysis based on the measured values of the instruments installed in the plant to determine the enthalpy at each location, the flow rate of the turbine extraction pipe, etc.

The plant heat balance calculation unit 24 analyzes the heat balance of the plant based on the measurement values acquired by the measurement value input unit 21, and calculates the enthalpy of each location to be assigned to the virtual variables, the flow rate of the turbine extraction pipe, etc., and sets these as the measurement values of the virtual variables 12 of the true value estimation unit 10.

As a result, the accuracy of the estimated true value yi of the plant instrumentation device 1 is improved, which in turn improves the accuracy of the expected degradation variables, thereby improving the accuracy of the equipment degradation judgment device 31 in judging the degradation state of the plant.

Next, another configuration of the plant instrumentation device 1 for improving the accuracy of the estimated true value yi will be described.
FIG. 6 is a configuration diagram of an equipment deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

The plant instrumentation device 1 in FIG. 6 is configured by adding a pressure balance model setting unit 25 to the plant instrumentation device 1 described in FIG. 2. The rest of the configuration is the same as in FIG. 2, so the description is omitted here. Note that the plant instrumentation device 1 in FIG. 4 may also be configured by adding a pressure balance model setting unit 25.

The pressure balance model setting unit 25 incorporates pressure models such as the pressure characteristics inside the turbine related to the measurement variables, the pressure loss calculation formula for the piping and equipment, and the pressure loss calculation formula associated with the opening degree of the control valve into the true value estimation unit 10 as constraint conditions 13. This improves the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

Based on the measurement values acquired by the measurement value input unit 21, the pressure balance model setting unit 25 analyzes the pressure characteristics inside the turbine, the pressure loss calculation formula for the piping and equipment, and the pressure loss calculation formula associated with the opening degree of the regulator valve, to calculate a value corresponding to the measurement variable 11, and sets this as the new measurement value of the measurement variable 11. This makes it possible to give redundancy to the measurement variable 11 that does not have redundancy, or to increase the redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

Next, another configuration of the plant instrumentation system 1 for improving the accuracy of the estimated true value yi will be described.
FIG. 7 is a configuration diagram of an equipment deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

The plant instrumentation device 1 in FIG. 7 is configured by adding a statistical model setting unit 26 to the plant instrumentation device 1 described in FIG. 2. The rest of the configuration is the same as in FIG. 2, so the description is omitted here. Note that the plant instrumentation device 1 in FIG. 4 may also be configured by adding a statistical model setting unit 26.

The statistical model setting unit 26 sets a statistical model represented by a relational equation of the measurement variables of the instruments obtained based on the measurement values of the normal operation data of the plant, and incorporates the relational equation of the statistical model into the true value estimation unit 10 as a constraint condition 13. This improves the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

The statistical model setting unit 26 also finds a statistical model represented by a relational equation of the measurement variables of the instruments calculated based on the measurement values of the normal operation data of the plant, calculates a value corresponding to the measurement variable 11 using the statistical model, and sets this as a new measurement value of the measurement variable 11. This makes it possible to give redundancy to the measurement variable 11 that does not have redundancy, or to increase the redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

The statistical model setting unit 26 may also import the estimated true values of the measured variables or virtual variables obtained by the true value estimation unit 10 and use them as inputs to the statistical model.

The equipment deterioration determination device 31 may have a model similar to the statistical model set by the statistical model setting unit 26, and may analyze the model using expected deterioration variables to perform an equipment deterioration assessment.

Next, another configuration of the plant instrumentation system 1 for improving the accuracy of the estimated true value yi will be described.
FIG. 8 is a configuration diagram of an equipment deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

The plant instrumentation device 1 in FIG. 8 is configured by adding a simulator setting unit 27 to the plant instrumentation device 1 described in FIG. 2. The rest of the configuration is the same as in FIG. 2, so the description is omitted here. Note that the plant instrumentation device 1 in FIG. 4 may also be configured by adding a simulator setting unit 27.

The simulator setting unit 27 sets an analysis simulator that simulates the plant behavior, and incorporates the calculation formula of the analysis simulator into the true value estimation unit 10 as a constraint condition 13. This improves the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

The simulator setting unit 27 also performs a simulation using the measurement values acquired by the measurement value input unit 21 to calculate a value corresponding to the measurement variable 11, and sets this as a new measurement value of the measurement variable 11. This makes it possible to give redundancy to the measurement variable 11 that does not have redundancy, or to increase the redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

The simulator setting unit 27 may also import the estimated true values of the measured variables or virtual variables obtained by the true value estimation unit 10 and use them as input to the analysis simulator.

The equipment deterioration judgment device 31 may have a simulator similar to the analysis simulator set by the simulator setting unit 27, and may perform a simulation using expected deterioration variables to evaluate the deterioration of the equipment.

Next, a plant maintenance optimization system including the plant instrumentation device 1 of the embodiment will be described.
The plant maintenance optimization system is a system that levels out the amount of inspection work for instruments during regular inspections.

In detail, the plant maintenance optimization system predicts the time when the inspection threshold will be reached based on the increasing trend of the penalty value of each instrument, evaluates the inspection volume of the instrument in the next and subsequent regular inspections, and provides the inspection timing of each instrument so as to level out the inspection volume in each regular inspection. This optimization of the maintenance volume prevents the concentration of instrument inspections at a certain regular inspection, which leads to increased costs due to an increase in the workload.

As shown in FIG. 9, if the penalty values of instruments A and B are predicted to reach the threshold value at the same time, for example, by inspecting instrument B early, the penalty values of instruments A and B will reach the threshold value at different times, thereby preventing the concentration of inspection work on instruments A and B.

Figure 10 is a configuration diagram of a plant maintenance optimization system equipped with a plant instrumentation device 1 according to an embodiment.

The plant instrumentation device 1 in FIG. 10 is configured by adding the plant heat balance calculation unit 24 described in FIG. 5, the pressure balance model setting unit 25 described in FIG. 6, the statistical model setting unit 26 described in FIG. 7, and the simulator setting unit 27 described in FIG. 8 to the plant instrumentation device 1 described in FIG. 4. Each configuration is similar to that described above, so the description will be omitted here.

In addition, in the plant maintenance optimization system of the embodiment, the plant heat balance calculation unit 24, the pressure balance model setting unit 25, the statistical model setting unit 26, and the simulator setting unit 27 may be omitted, or any of the configurations may be included.

The plant maintenance optimization system is equipped with a maintenance quantity optimization device 33, which optimizes the maintenance quantity based on the output of the equipment deterioration/meter drift judgment device 32 and the penalty value.

Next, we will explain how the penalty values are handled in the equipment deterioration determination device 31, the equipment deterioration/meter drift determination device 32, and the maintenance quantity optimization device 33.

For status monitoring purposes of the equipment deterioration judgment device 31 and the equipment deterioration/instrument drift judgment device 32, for example, the penalty value threshold is set to 1.96^2. This corresponds to the deviation between the actual measurement value and the estimated true value of the instrument deviating from the 95% confidence interval when the measurement variability of the target instrument is normal, meaning that the target instrument contains a drift error that is not statistically acceptable. To detect instrument drift at an earlier stage, the penalty value threshold may be set to 1.0^2. This corresponds to the deviation between the actual measurement value and the estimated true value of the instrument deviating from the 68% confidence interval. When the penalty value of each instrument reaches these thresholds, or is expected to reach the thresholds, an inspection of the target instrument is prompted.

Furthermore, in trend monitoring applications of the maintenance quantity optimization device 33, as shown in FIG. 9, the timing of inspection of each instrument can be estimated in advance from the increasing trend of the penalty value. Therefore, for particularly important instruments, by monitoring the increasing trend of the penalty value, even if the penalty value does not reach the threshold value, if a clear increasing trend is observed, an inspection of the target instrument is prompted.

In addition, by predicting the inspection timing based on the monitoring results of the maintenance quantity optimization device 33 and planning the inspection timing of each instrumentation item so as to level out the maintenance quantity of the instruments at each regular inspection, it is possible to suppress increases in maintenance costs and optimize maintenance.

Furthermore, the present invention is not limited to the above-mentioned examples, but includes various modified examples. The above-mentioned examples have been described in detail to provide an easy-to-understand explanation of the present invention, and are not necessarily limited to those having all of the configurations described. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment.

REFERENCE SIGNS LIST 1 Plant instrumentation device 10 True value estimation unit 11 Measurement variable 12 Virtual variable 13 Constraint condition 14 DR processing unit 15 Penalty value calculation unit 21 Measurement value input unit 22 Virtual variable setting unit 23 Constraint condition setting unit 24 Plant heat balance calculation unit 25 Pressure balance model setting unit 26 Statistical model setting unit 27 Simulator setting unit 31 Equipment deterioration determination device 32 Equipment deterioration/instrument drift determination device 33 Maintenance quantity optimization device

Claims (8)

An equipment deterioration monitoring system including a plant instrumentation device for determining a state of equipment or an instrument used in a power plant,
The plant instrumentation device includes:
a measurement value input unit that inputs actual measurement values of meters installed in the plant as measurement values of measurement variables;
a virtual variable setting unit that sets measurement information of a virtual instrument virtually installed in the plant as a virtual variable;
a constraint condition setting unit for setting a constraint condition related to the measurement variable or the virtual variable;
a true value estimating unit that calculates estimated true values of the measurement variables and the virtual variables from the measurement variables, the virtual variables, and the constraint conditions by a least squares method using uncertainties of the measurement variables as weights so as to minimize deviations between the measurement values of the measurement variables and the virtual variables;
The virtual variables are assumed to be assumed deterioration variables indicating deterioration states of equipment at assumed locations of the plant equipment ,
An equipment deterioration monitoring system comprising an equipment deterioration judgment device that determines whether an estimated true value of an assumed deterioration variable calculated by the plant instrumentation device is equal to or greater than a threshold value, and judges that deterioration has occurred in the equipment corresponding to the assumed deterioration variable if the estimated true value is equal to or greater than the threshold value. An equipment deterioration monitoring system including a plant instrumentation device for determining a state of equipment or an instrument used in a power plant,
The plant instrumentation device includes:
a measurement value input unit that inputs actual measurement values of meters installed in the plant as measurement values of measurement variables;
a virtual variable setting unit that sets measurement information of a virtual instrument virtually installed in the plant as a virtual variable;
a constraint condition setting unit for setting a constraint condition related to the measurement variable or the virtual variable;
a true value estimation unit that calculates estimated true values of the measurement variables and the virtual variables from the measurement variables, the virtual variables, and the constraint conditions by a least squares method using uncertainties of the measurement variables as weights so that deviations between the measurement values of the measurement variables and the virtual variables are minimized;
a penalty value calculation unit that sets the virtual variable as an assumed deterioration variable indicating a deterioration state of equipment at an assumed location of the plant equipment, and calculates a deviation between an estimated true value of the measurement variable and a measurement value of an instrument input by the measurement value input unit as a penalty value,
An equipment deterioration monitoring system comprising an equipment deterioration/instrument drift determining device that determines the drift of an instrument based on an estimated true value of an assumed deterioration variable calculated by the plant instrumentation device and the penalty value. In the facility deterioration monitoring system according to claim 1 or 2 ,
the virtual variable setting unit sets a flow rate of a turbine extraction pipe to the virtual variable;
13. An equipment deterioration monitoring system comprising: a plant heat balance calculation unit that analyzes the heat balance of a plant to obtain measured values of the virtual variables. In the facility deterioration monitoring system according to claim 1 or 2 ,
An equipment deterioration monitoring system characterized by comprising a pressure balance model setting unit that sets a pressure model such as the pressure characteristics inside the turbine, a pressure loss calculation formula for piping and equipment, or a pressure loss calculation formula associated with the opening of a control valve, related to the measurement variables, as a constraint condition, or analyzes a pressure model such as the pressure characteristics inside the turbine, a pressure loss calculation formula for piping and equipment, or a pressure loss calculation formula associated with the opening of a control valve , related to the measurement variables, using the measurement values of the instruments input by the measurement value input unit, and calculates the value as a new measurement value of the measurement variable. In the facility deterioration monitoring system according to claim 1 or 2 ,
An equipment deterioration monitoring system comprising a statistical model setting unit that sets a statistical model represented by a relational equation of measurement variables of an instrument obtained based on measurement values of normal operation data of a plant, and sets the relational equation of the statistical model as a constraint condition, or calculates a value corresponding to the measurement variable using the statistical model and sets this as a new measurement value of the measurement variable. 6. The facility deterioration monitoring system according to claim 5 ,
The facility deterioration monitoring system according to the present invention, wherein the statistical model setting unit inputs estimated true values of the measurement variables or virtual variables into the statistical model. In the facility deterioration monitoring system according to claim 1 or 2 ,
An equipment deterioration monitoring system comprising a simulator setting unit that sets an analysis simulator that simulates plant behavior, and sets the calculation formula of the analysis simulator as a constraint condition, or performs a simulation using the analysis simulator based on the measurement values of an instrument input by the measurement value input unit to obtain values of measurement variables, and sets these values as new measurement values of the measurement variables. In the facility deterioration monitoring system according to claim 7 ,
The facility deterioration monitoring system is characterized in that the simulator setting unit inputs estimated true values of the measurement variables or virtual variables into the analysis simulator.

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