Plant facility deterioration monitoring method and plant facility deterioration monitoring system

Abstract

To provide a widely applicable, highly accurate facility deterioration monitoring system.SOLUTION: A facility deterioration monitoring system includes a plant instrumentation device that obtains the state of a plant facility or instrument used at a power generating plant. The plant measurement device 1 has: a measurement value input part 21 that inputs, as a measurement value of a measurement variable, an actually measured value of the instrument set at the plant; a virtual variable setting part 22 that sets, as a virtual variable, measurement information of the virtual instrument virtually set at the plant; a constraint condition setting part 23 that sets constraint conditions related to the measurement variable or the virtual variable; and a true value estimation part 10 that, based on the measurement variable 11, the virtual variable 12, and the constraint conditions 13, calculates an estimated true value of the measurement variable and the virtual variable through the least squares method weighted by uncertainty of the measurement variable so that deviation in the measurement values of the measurement variable and the virtual variable becomes minimum. The virtual variable is defined as an assumed deterioration variable indicating deterioration state of the device facility at an assumed site of the plant facility.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a facility deterioration monitoring system using a data reconciliation technique. [Background technology]

[0002] The equipment and instruments used in power plants deteriorate over time. For example, valve seat leaks occur, the heat transfer performance of heat exchangers decreases due to fouling of heat transfer tubes, and the flow meter readings drift due to rust on the flow nozzle surface of the flow meter. Such deterioration of plant equipment and devices is a factor that reduces the power generation efficiency of thermal and nuclear power plants.

[0003] When a decrease in power generation efficiency occurs during operation, it is necessary to identify from the parameters during plant operation whether the cause is deterioration of the plant equipment or instruments due to steam leaks, 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.

[0004] For this reason, various techniques for identifying the deterioration factors of plant equipment and instruments have been proposed. 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 for comprehensively evaluating each estimated true value from data related to accuracy and a data reconciliation technique as a consistency improvement means for calculating an estimated true value that is consistent as a system, the most likely estimated true value is obtained, and an estimated drift amount of the instrument can be calculated to identify the cause of performance deterioration, and it is also shown that aging and performance deterioration of the equipment can be evaluated.

[0005] The use of data reconciliation technology enables more efficient and reliable analysis than estimating 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. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2005-338049 A Summary of the Invention [Problem to be solved by the invention]

[0007] According to the technology of Patent Document 1, it is possible to evaluate the aging and performance degradation of equipment based on the actual measured values ​​of each detector signal of a plant. However, there are problems that make it impossible to apply the technology of Patent Document 1, such as the fact that a method for detecting valve seat leaks that cause power generation loss based on the actual measured values ​​of detector signals has not been established, the fact that a baseline method for performing high-precision data reconciliation evaluation has not been established, and the fact that data reconciliation evaluation cannot be performed when there is no redundancy in the detector.

[0008] 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. [Means for solving the problem]

[0009] 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. Effect of the Invention

[0010] According to the present invention, it is possible to provide a highly accurate facility deterioration monitoring system with a wide range of applications. [Brief description of the drawings]

[0011] [Figure 1A] FIG. 1 is a diagram illustrating a specific example before application of DR technology. [Figure 1B] FIG. 13 is a diagram showing a specific example after application of DR technology. [Diagram 2] FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Diagram 3] FIG. 1 is a schematic diagram of a secondary cooling system for a nuclear reactor plant. [Figure 4] FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Diagram 5] FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 6] FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 7] FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 8] FIG. 1 is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 9] FIG. 2 is a diagram illustrating the operation of the plant maintenance optimization system. [Figure 10] FIG. 1 is a configuration diagram of a plant maintenance optimization system equipped with a plant instrumentation device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment 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.

[0013] 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., sensors that are installed multiple times to detect the same parameters, and estimates highly reliable true values ​​by satisfying conservation laws between instruments.

[0014] In detail, when each instrument in a plant is i, the measurement value (actual value) of each instrument is xi, the estimated true value is yi, the uncertainty of each measurement value is σi, the objective function is J(yi), and the constraint is f(yi), the DR technology calculates the estimated true value yi of the best process, which is the solution to the two simultaneous equations in Equation 1, by using the least squares method with the uncertainty of the measurement value as the weight so that the deviation between the measurement value xi and the estimated true value yi is minimized.

[0015]

number

[0016] 1A and 1B are diagrams showing specific examples before and after the application of DR technology. Note that (t / h) in Fig. 1A and Fig. 1B indicates mass flow rate (tons / hour).

[0017] The flow rate measurement values ​​of meters A, B, and C before the application of DR technology shown in Figure 1A 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.

[0018] 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 and estimated error range σi (uncertainty) of the flow rate at the installation locations of meters A, B, and C. 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.

[0019] 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, that is, 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 plant deterioration 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.

[0020] 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 variable of the DR technology, and serves as a baseline for high-precision evaluation.

[0021] Furthermore, the plant instrumentation device of the embodiment applies statistical models such as pressure balance calculations of the pressure characteristics inside the turbine of the plant, pressure losses in piping and equipment, and relationships between instruments obtained based on past normal operation data, and internal calculation formulas of a simulator that simulates plant behavior as constraints to the DR technology, or applies the outputs of these as measurement values ​​xi to the DR technology, 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. EXAMPLES

[0022] FIG. 2 is a configuration diagram of a facility deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

[0023] 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 each instrument signal in the plant, the valve seat leakage amount, the heat exchanger tube leakage amount, the amount of deterioration in the heat transfer performance of the heat exchanger, the heat exchanger tube leakage amount, the amount of deterioration in pump performance, etc. to DR technology as virtual 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.

[0024] Here, the assumed deterioration 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 leakage from heat exchanger tubes, the amount of reduction in pump head, etc. are quantitative virtual variables that correspond to the assumed type of deterioration of plant equipment.

[0025] In addition to the actual measured values ​​of each instrument in the plant, the plant instrumentation device 1 sets an assumed degradation variable as a measured value of a virtual instrument at a location in the plant where degradation is assumed to occur, and estimates the true value of the assumed degradation variable by applying DR technology. Then, the equipment degradation determination device 31 determines the degradation of equipment and facilities from the fluctuation of the assumed degradation variable estimated by the plant instrumentation device 1. The plant instrumentation device 1 may also use the drift amount of the instrument as the assumed degradation variable. Furthermore, in the case of the heat transfer performance of a heater, a decrease in the outlet temperature of the non-heating side fluid or an increase in the drain temperature of the heating side fluid may be used as a quantitative assumed degradation variable.

[0026] A specific example will be described using the schematic diagram of the secondary cooling system of a nuclear reactor plant in Fig. 3. In the secondary cooling system of Fig. 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 the 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.

[0027] 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 are X1 = 0, X2 = 0, and X3 = 0 (t / h). If the assumed degradation variables X1 = 20, X2 = 0, and X3 = 0 (t / h) 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 the assumed degradation variable X1 is set, causing the decrease in power generation.

[0028] Returning to FIG. 2, the configuration of the equipment 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.

[0029] The plant instrumentation device 1 comprises a measurement value input unit 21, a virtual variable setting unit 22, a constraint condition setting unit 23, and a true value estimating unit 10.

[0030] The measurement value input unit 21 acquires the actual measurement values ​​of the instruments in the plant, and notifies the true value estimation unit 10 of the measured values ​​as the measurement variables.

[0031] The virtual variable setting unit 22 sets virtual variables (assumed degradation variables) to be incorporated into the true value estimation unit 10.

[0032] The constraint condition setting unit 23 sets the conservation law or balance law of variables (measurement variables and virtual variables) when the true value estimation unit 10 calculates the estimated true value as a constraint condition in the DR technique.

[0033] The true value estimation unit 10 is composed of a storage unit for storing information on measurement variables 11, virtual variables 12, and constraint conditions 13, and a DR processing unit .

[0034] The measurement variables 11 store the actual measured values ​​of the instruments of the plant notified from the measurement value input unit 21 as measured values ​​for processing in the DR processor 14, and also indicate estimated true values ​​calculated by the DR processor 14.

[0035] The virtual variables 12 are set by a virtual variable setting unit 22, store virtual measured values ​​of the virtual variables in the DR processing unit 14, and indicate estimated true values ​​calculated by the DR processing unit 14.

[0036] The constraint condition 13 stores constraint conditions in the DR technique set by the constraint condition setting unit 23 .

[0037] The DR processor 14 is a processor that calculates the estimated true values ​​yi of the measurement variables 11 and the virtual variables 12 according to the above-mentioned formula 1. The DR processor 14 sets the accuracy of each instrument in the plant as the uncertainty σi.

[0038] Specifically, the plant instrumentation device 1 is configured by a computer consisting of a CPU that performs arithmetic 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, the virtual variables 12, and the constraint conditions 13 are configured in the memory.

[0039] The equipment deterioration determination 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 value. If the assumed deterioration variables X1, X2, and X3 are equal to or greater than the threshold value, it is determined that deterioration has occurred in the equipment at the assumed location.

[0040] As described above, the equipment deterioration monitoring system according to the embodiment can grasp deterioration at a location where no instrument is actually installed, based on the assumed deterioration variable estimated by the plant instrumentation device 1. EXAMPLES

[0041] Next, a configuration of a facility deterioration monitoring system according to an embodiment for detecting and determining both deterioration of equipment and drift of meters will be described.

[0042] FIG. 4 is a system configuration diagram of a facility deterioration monitoring system including a plant instrumentation device 1 according to an 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, so descriptions thereof will be omitted here.

[0043] 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

[0044] The penalty value indicates the degree of deviation between the instrument's measurement (actual measurement) and the estimated true value. Therefore, even if the power generation or the equipment around the target instrument is sound, if the penalty value becomes large, that is, if the deviation of the target instrument's actual measurement value from the likely estimated true value becomes large, it indicates that there is a high possibility that instrument drift is occurring.

[0045] The equipment deterioration / instrument drift judgment device 32 detects and judges the deterioration of the equipment when the assumed deterioration variable of the plant instrumentation device 1 changes, and detects and judges the drift of the instrument when the penalty value fluctuates. This enables the equipment deterioration monitoring system to grasp the deterioration state of the plant in detail. EXAMPLES

[0046] Next, a 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 a facility deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

[0047] 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. Other configurations are similar to those in Fig. 2, and therefore will not be described here. Note that the plant instrumentation device 1 in Fig. 4 may be configured by adding the plant heat balance calculation unit 24.

[0048] The plant instrumentation device 1 is provided with a plant heat balance calculation unit 24 which treats 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 measurement values ​​of the instruments installed in the plant to determine the enthalpy at each location, the flow rate of the turbine extraction pipe, etc.

[0049] 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 determines 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 measurement values ​​of the virtual variables 12 of the true value estimation unit 10.

[0050] 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 assumed deterioration variables, thereby improving the accuracy with which the equipment deterioration determining device 31 determines the deterioration state of the plant. EXAMPLES

[0051] 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 a facility deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

[0052] 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. Other configurations are similar to those in Fig. 2, and therefore will not be described here. Note that the plant instrumentation device 1 in Fig. 4 may be configured by adding the pressure balance model setting unit 25.

[0053] The pressure balance model setting unit 25 incorporates pressure models such as pressure characteristics in the turbine related to the measurement variables, a pressure loss calculation formula for the piping and equipment, and a pressure loss calculation formula related to the opening degree of the regulator 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.

[0054] Furthermore, the pressure balance model setting unit 25 analyzes the pressure characteristics in the turbine, the pressure loss calculation formula for the piping and equipment, and the pressure loss calculation formula associated with the opening of the regulator valve, based on the measurement values ​​acquired by the measurement value input unit 21, calculates 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 has no redundancy, or to increase the redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10. EXAMPLES

[0055] Next, another configuration of the plant instrumentation device 1 for improving the accuracy of the estimated true value yi will be described. FIG. 7 is a configuration diagram of a facility deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

[0056] 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. Other configurations are similar to those in Fig. 2, and therefore will not be described here. Note that the plant instrumentation device 1 in Fig. 4 may also be configured by adding the statistical model setting unit 26.

[0057] The statistical model setting unit 26 sets a statistical model represented by a relational expression of measurement variables of instruments obtained based on the measurement values ​​of normal operation data of the plant, and incorporates the relational expression 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.

[0058] Furthermore, the statistical model setting unit 26 obtains a statistical model indicated by a relational expression of the measurement variables of the instruments obtained 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 value as a new measurement value of the measurement variable 11. This makes it possible to give redundancy to the measurement variable 11 that has no redundancy or to increase the redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

[0059] Furthermore, the statistical model setting section 26 may take in the estimated true values ​​of the measured variables or virtual variables obtained by the true value estimating section 10 and use them as inputs to the statistical model.

[0060] 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 assumed deterioration variables to perform deterioration evaluation of the equipment. EXAMPLES

[0061] Next, another configuration of the plant instrumentation device 1 for improving the accuracy of the estimated true value yi will be described. FIG. 8 is a configuration diagram of a facility deterioration monitoring system including a plant instrumentation device 1 according to an embodiment.

[0062] 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. Other configurations are similar to those in Fig. 2, and therefore will not be described here. Note that the plant instrumentation device 1 in Fig. 4 may be configured by adding the simulator setting unit 27.

[0063] The simulator setting unit 27 sets an analysis simulator that simulates the plant behavior, and incorporates a 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.

[0064] Moreover, the simulator setting unit 27 performs a simulation using the measurement values ​​acquired by the measurement value input unit 21, calculates 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 impart redundancy to the measurement variable 11 that has no redundancy, or to increase the redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.

[0065] The simulator setting section 27 may also take in the estimated true values ​​of the measured variables or virtual variables obtained by the true value estimating section 10 and use them as input to the analysis simulator.

[0066] The equipment deterioration determination device 31 may have a simulator similar to the analysis simulator set by the simulator setting unit 27, and may perform a simulation using assumed deterioration variables to perform deterioration evaluation of the equipment. EXAMPLES

[0067] 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.

[0068] In detail, the plant maintenance optimization system predicts the time to reach the inspection threshold from 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 occurrence of cost increases due to an increase in the workload caused by the concentration of instrument inspections at a certain regular inspection.

[0069] As shown in Figure 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.

[0070] FIG. 10 is a configuration diagram of a plant maintenance optimization system including a plant instrumentation device 1 according to an embodiment.

[0071] 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 description thereof will be omitted here.

[0072] 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 the system may have any of the configurations.

[0073] The plant maintenance optimization system includes a maintenance quantity optimization device 33, which optimizes the maintenance quantity based on the output of the equipment deterioration / meter drift determination device 32 and the penalty value.

[0074] Next, the handling of penalty values ​​in the equipment deterioration determination device 31, the equipment deterioration / meter drift determination device 32, and the maintenance quantity optimization device 33 will be described.

[0075] For the purpose of monitoring the condition 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 tolerable. 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.

[0076] Furthermore, in the trend monitoring application of the maintenance quantity optimization device 33, the inspection timing of each instrument can be estimated in advance from the increasing trend of the penalty value, as shown in Fig. 9. 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, the inspection of the target instrument is prompted.

[0077] 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.

[0078] Furthermore, the present invention is not limited to the above-mentioned examples, and various modified examples are included. The above-mentioned examples have been described in detail to easily explain the present invention, and the present invention is not necessarily limited to those having all of the configurations described. Furthermore, it is possible to replace a 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. [Explanation of symbols]

[0079] 1 Plant Instrumentation 10 True value estimation section 11 Measurement variables 12 Virtual Variables 13 Constraints 14 DR Processing Section 15 Penalty value calculation unit 21 Measurement value input section 22 Virtual variable setting section 23 Constraint Condition Setting Section 24 Plant heat balance calculation section 25 Pressure balance model setting section 26 Statistical Model Setting Section 27 Simulator Settings 31 Equipment deterioration judgment device 32 Equipment Deterioration and Instrument Drift Judgment Device 33 Maintenance quantity optimization device

Claims

[Claim 1] 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.

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