Plant equipment deterioration monitoring method and plant equipment deterioration monitoring system
The system enhances data reconciliation technology by using redundancy and virtual variables to accurately detect plant equipment deterioration, improving maintenance efficiency and reducing losses.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- HITACHI GE NUCLEAR ENERGY LTD
- Filing Date
- 2025-03-21
- Publication Date
- 2026-07-30
AI Technical Summary
Existing methods for identifying plant equipment deterioration, such as valve seat leaks and instrument drift, lack a defined method for high-precision data reconciliation evaluation and are ineffective when detectors lack redundancy.
A system that calculates estimated true values using data reconciliation technology, incorporating redundancy from multiple sensors and virtual variables, and applies constraints like conservation laws and statistical models to enhance accuracy.
Provides a highly accurate method for monitoring plant equipment deterioration, enabling precise detection of issues like steam leaks and instrument drift, thereby optimizing maintenance and reducing power generation losses.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to Plant equipment deterioration monitoring method using data reconciliation technology.
Background Art
[0002] Plant facilities and instruments used in power generation 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 indicated value of a flow meter drifts due to rust adhesion on the surface of the flow nozzle of the flow meter. Such deterioration of plant facilities and equipment becomes a factor in reducing the power generation efficiency of thermal and nuclear power generation.
[0003] When a decrease in power generation efficiency occurs during operation, it is necessary to identify whether the deterioration of plant facilities and instruments, which is the cause, is steam leakage, equipment deterioration, or instrument drift, from the parameters during plant operation. Identifying the cause of the decrease in power generation efficiency and performing appropriate maintenance is important for maintaining a high power generation efficiency in thermal and nuclear power generation.
[0004] For this reason, various techniques for identifying the deterioration factors of plant facilities and instruments have been conventionally devised. For example, in Patent Document 1, a true value is estimated based on the measured values of the detector signals of each plant using a unique true value estimation model. Then, by using data reconciliation technology, which is an estimated true value integration means for comprehensively evaluating each estimated true value from data related to accuracy and a consistency improvement means for calculating an estimated true value that is consistent as a system, the most probable estimated true value is obtained, and thus the estimated drift amount of the instrument can be calculated to identify the performance degradation factor. It is also shown that the evaluation of the aging change and performance degradation of equipment can be performed.
[0005] By using data reconciliation technology, more efficient and reliable analysis becomes possible 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, thereby reducing power generation losses at the plant. [Prior art documents] [Patent Documents]
[0006] [Patent Document 1] Japanese Patent Publication No. 2005-338049 [Overview of the project] [Problems that the invention aims to solve]
[0007] According to the technology described in Patent Document 1, it is possible to evaluate the aging and performance degradation of equipment based on the measured values of the detector signals in a plant. However, there were problems in applying the technology described in Patent Document 1, such as the lack of a defined method for detecting valve seat leaks that result in power generation losses based on the measured values of the detector signals, the lack of a defined baseline method for performing high-precision data reconciliation evaluation, and the inability to perform data reconciliation evaluation if the detectors lack redundancy.
[0008] The objective of the present invention is to solve the above problems and to provide a highly accurate product with a wide range of applications. Plant equipment deterioration monitoring method The objective is to provide. [Means for solving the problem]
[0009] The present invention relates to calculating the estimated true value of a measured value from a measured value acquired by an instrument in a power plant, an assumed degradation variable set for a location in the power plant where degradation is expected, and constraints relating to the measured value and the assumed degradation variable, and to calculating a penalty value from the estimated true value of the measured value and the measured value. [Effects of the Invention]
[0010] According to the present invention, a highly accurate system with a wide range of applications Plant equipment deterioration monitoring method We can provide this. [Brief explanation of the drawing]
[0011] [Figure 1A] It is a diagram showing a specific example before the application of DR technology. [Figure 1B] It is a diagram showing a specific example after the application of DR technology. [Figure 2] It is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 3] It is a schematic diagram of the secondary cooling system of a nuclear power plant. [Figure 4] It is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 5] It is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 6] It is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 7] It is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 8] It is a configuration diagram of an equipment deterioration monitoring system equipped with a plant instrumentation device. [Figure 9] It is a diagram for explaining the operation of a plant maintenance optimization system. [Figure 10] It is a configuration diagram of a plant maintenance optimization system equipped with a plant instrumentation device.
Embodiments for Carrying Out the Invention
[0012] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. First, the data reconciliation technology (referred to as DR technology) 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 the information of existing sensors installed in multiple numbers to detect the same parameter, that is, it has redundancy, and satisfies the conservation law between instruments to estimate a highly reliable true value.
[0014] Specifically, when the DR technology sets each instrument in the plant as i, the measured value (actual measured value) of each instrument as xi, the estimated true value as yi, the uncertainty of each measured value as σi, the objective function as J(yi), and the constraint condition as f(yi), the estimated true value yi of the best process, which is the solution of the simultaneous equations of the two equations in Equation 1, is calculated by the least squares method with the uncertainty of the measured value as the weight so that the deviation between the measured value xi and the estimated true value yi is minimized.
[0015]
Number
[0016] Figures 1A and 1B are diagrams showing specific examples before and after the application of the DR technology. Note that (t / h) in Figures 1A and 1B indicates the mass flow rate (tons / hour).
[0017] The flow rate measurement values of instruments A, B, and C before the application of the DR technology shown in Figure 1A do not match on the inlet side and the outlet side of the container. This is because each instrument has a measurement error when there is no leak from the container.
[0018] Based on the instrument errors and the measured values xi of instruments A, B, and C in Figure 1A, when the DR technology is applied, the estimated true values yi and the estimated error ranges σi (uncertainties) of the flow rates at the installation locations of instruments A, B, and C can be obtained. As shown in Figure 1B, the estimated true values yi of the flow rates match on the inlet and outlet sides of the container, and the measurement errors of each of instruments A, B, and C are also reduced.
[0019] Focusing on the principle that the plant instrumentation device of the embodiment can calculate the estimated true value yi of the instrument by using the information of the existing designed instruments installed in multiple numbers to detect the redundancy of the instrument, that is, the same parameter, and satisfying the conservation law between the instruments, the plant instrumentation device incorporates information that cannot be detected such as steam leaks or measured values related to assumed deterioration of the plant as virtual variables into the DR technology, and incorporates the conservation law or the balance law of the virtual variables as constraint conditions into the DR technology to estimate the true value.
[0020] Furthermore, the plant instrumentation system of this embodiment uses the output of the plant thermal balance calculation as the measured value of the virtual variable of the DR technology, and uses it as a baseline for high-precision evaluation.
[0021] Furthermore, the plant instrumentation system of the embodiment improves the scope of application of DR technology by applying DR technology with constraints such as pressure balance calculations including the pressure characteristics inside the plant turbine and pressure drops in piping and equipment, statistical models that incorporate the relationships between instruments obtained based on past normal operating data, and internal calculation formulas of a simulator that simulates plant behavior, or by applying these outputs to DR technology as measured values xi to increase redundancy. The configuration of the plant instrumentation system in this embodiment will be described in more detail below. [Examples]
[0022] Figure 2 is a diagram showing the configuration of an equipment deterioration monitoring system equipped with a plant instrumentation device 1 according to an embodiment.
[0023] The equipment degradation monitoring system shown in Figure 2 is applied to the operation management of thermal and nuclear power plants. It applies measurement variables based on the signals of various instruments within the plant, along with virtual variables (hereinafter referred to as assumed degradation variables) such as valve seat leak rate, heat exchange tube leak rate, heat exchanger heat transfer performance degradation rate, heat exchanger tube leak rate, and pump performance degradation rate, to DR technology. The equipment degradation of plant equipment is determined based on the values of the assumed degradation variables estimated by DR technology.
[0024] Here, we will explain in more detail the assumed degradation variables (virtual variables) in Example 1. Assumed degradation variables are measured values taken by virtual instruments in the plant, where no actual instruments are installed, and are virtual variables of DR technology that assume the degradation state of the equipment. For example, the amount of valve seat leak at various points in the power plant, the amount of heat transfer performance reduction of heat exchangers, the amount of heat exchanger tube leak, the amount of pump head reduction, etc., are used as quantitative virtual variables according to the assumed type of degradation of the plant equipment.
[0025] The plant instrumentation device 1, in addition to the actual measured values of each instrument in the plant, sets assumed degradation variables as measured values of virtual instruments at locations in the plant where degradation is anticipated, and applies DR technology to estimate the true values of the assumed degradation variables. The equipment degradation judgment device 31 then determines the degradation of the equipment based on the fluctuations of the assumed degradation variables estimated by the plant instrumentation device 1. The plant instrumentation device 1 may also use the amount of instrument drift as an assumed degradation variable. Furthermore, in the case of the heat transfer performance of a heater, the decrease in the outlet temperature of the non-heated fluid or the increase in the drain temperature of the heated fluid may be used as quantitative assumed degradation variables.
[0026] A concrete example will be explained using the schematic diagram of the secondary cooling system of a nuclear reactor plant shown 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 decrease in 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 decrease in heat transfer performance of the heat exchanger is defined as the assumed degradation variable X3.
[0027] If the assumed degradation variables X1, X2, and X3 are in a healthy state, then when DR technology is applied to the overall conservation law calculation, the assumed degradation variables X1 = 0, X2 = 0, and X3 = 0 (t / h). If the power generation decreases and the result of the assumed degradation variables X1 = 20, X2 = 0, and X3 = 0 (t / h), then it can be estimated that a steam leak of 20 (t / h) occurred in the flow path from the reactor to the turbine, where the assumed degradation variable X1 was set, resulting in a decrease in power generation.
[0028] Returning to Figure 2, we will explain the configuration of the equipment deterioration monitoring system. The equipment deterioration monitoring system consists of a plant instrumentation device 1 that calculates assumed deterioration variables based on information from plant instruments, and an equipment deterioration determination device 31 that determines equipment deterioration from the assumed deterioration variables.
[0029] The plant instrumentation device 1 consists of a measurement value input unit 21, a virtual variable setting unit 22, a constraint condition setting unit 23, and a true value estimation unit 10.
[0030] The measurement input unit 21 acquires the actual measured values from each instrument in the plant and notifies the true value estimation unit 10 of the measured values of 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 setting unit 23 sets the conservation law or balance law of the variables (measured variables and virtual variables) used when the true value estimation unit 10 calculates the estimated true value as constraints in the DR technology.
[0033] The true value estimation unit 10 consists of a storage unit for information on the measurement variable 11, the virtual variable 12, and the constraint condition 13, and a DR processing unit 14.
[0034] The measurement variable 11 stores the actual measured values of each instrument in the plant, notified by the measurement value input unit 21, as the measured values processed in the DR processing unit 14, and also shows the estimated true value calculated by the DR processing unit 14.
[0035] The virtual variable 12 is set by the virtual variable setting unit 22, stores the virtual measured value of the virtual variable in the DR processing unit 14, and also shows the estimated true value calculated by the DR processing unit 14.
[0036] Constraint condition 13 stores the constraint conditions in the DR technology set by the constraint condition setting unit 23.
[0037] The DR processing unit 14 is a processing unit that calculates the estimated true value yi of the measured variable 11 and the virtual variable 12 according to the above formula 1. The DR processing unit 14 sets the accuracy of each instrument in the plant as uncertainty σi.
[0038] Specifically, the plant instrumentation device 1 is configured as a computer consisting of a CPU for calculation processing, memory, a communication unit, an operation unit, a display unit, and a non-volatile storage medium. The CPU executes a program stored in the non-volatile storage medium, which functions as a DR processing unit 14, a measured value input unit 21, a virtual variable setting unit 22, and a constraint condition setting unit 23. The measured variables 11, virtual variables 12, and constraint conditions 13 are configured in memory.
[0039] The equipment degradation judgment device 31 determines whether the assumed degradation variables X1, X2, and X3, calculated as estimated true values of virtual variables in the plant instrumentation device 1, are above a predetermined threshold. For assumed degradation variables X1, X2, and X3 that are above the threshold, it is determined that degradation has occurred in the equipment at the assumed location.
[0040] As described above, the equipment deterioration monitoring system of this embodiment can grasp the deterioration of areas where instruments are not actually installed, using assumed deterioration variables estimated by the plant instrumentation device 1. [Examples]
[0041] Next, we will describe the configuration of an equipment deterioration monitoring system in an embodiment that detects and determines both equipment deterioration and instrument drift.
[0042] Figure 4 is a system configuration diagram of an equipment deterioration monitoring system equipped with the plant instrumentation device 1 of the embodiment. The plant instrumentation device 1 in Figure 4 differs from the plant instrumentation device 1 in Figure 2 in that it includes a penalty value calculation unit 15. Other components are the same as in Figure 2, so their explanation is omitted here.
[0043] The penalty value calculation unit 15 calculates a penalty value for each instrument in the plant, based on the measured value (actual value xi) of the instrument acquired by the measurement value input unit 21 and the estimated true value yi of the measured value of the instrument estimated by the DR processing unit 14, using formula 2. Here, the uncertainty σi is determined from the instrument accuracy or the variability of the actual value. Penalty value = {(yi -xi) / σi}^2 …Formula 2
[0044] The penalty value indicates the degree of deviation between the instrument's measured value (actual value) and the estimated true value. Therefore, even if the power generation or the equipment surrounding the instrument in question is functioning correctly, a large penalty value—that is, a large deviation of the instrument's measured value from a likely estimated true value—indicates a high probability that instrument drift is occurring.
[0045] The equipment degradation / instrument drift determination device 32 detects and determines equipment degradation when the assumed degradation variable of the plant instrumentation device 1 changes, and detects and determines instrument drift when the penalty value changes. This allows the equipment degradation monitoring system to gain a detailed understanding of the plant's degradation status. [Examples]
[0046] Next, we will describe the configuration of the plant instrumentation device 1 that improves the accuracy of the estimated true value yi. Figure 5 is a diagram showing the configuration of an equipment deterioration monitoring system equipped with the plant instrumentation device 1 of the embodiment.
[0047] The plant instrumentation system 1 in Figure 5 is constructed by adding a plant thermal balance calculation unit 24 to the plant instrumentation system 1 described in Figure 2. Other components are the same as in Figure 2, so their explanation is omitted here. Alternatively, the plant instrumentation system 1 in Figure 4 may be constructed by adding a plant thermal balance calculation unit 24.
[0048] The plant instrumentation device 1 includes a plant thermal balance calculation unit 24 that uses virtual variables such as the enthalpy at each location where no instruments are installed, and the flow rate of the turbine extraction pipe, and analyzes them based on the measured values of instruments installed in the plant to determine the enthalpy at each location, the flow rate of the turbine extraction pipe, etc.
[0049] The plant thermal balance calculation unit 24 analyzes the thermal balance of the plant based on the measured values acquired by the measured value input unit 21, and determines the enthalpy of each location, the flow rate of the turbine extraction pipe, etc., to be assigned to virtual variables, and uses these as the measured values of the virtual variables 12 in the true value estimation unit 10.
[0050] As a result of the above, 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 degradation variables and thus improves the accuracy of the equipment degradation judgment device 31 in determining the degradation state of the plant. [Examples]
[0051] Next, we will describe other components of the plant instrumentation device 1 that improve the accuracy of the estimated true value yi. Figure 6 is a diagram showing the configuration of an equipment deterioration monitoring system equipped with the plant instrumentation device 1 of the embodiment.
[0052] The plant instrumentation system 1 in Figure 6 is constructed by adding a pressure balance model setting unit 25 to the plant instrumentation system 1 described in Figure 2. Other components are the same as in Figure 2, so their explanation is omitted here. Alternatively, the plant instrumentation system 1 in Figure 4 may be constructed by adding a pressure balance model setting unit 25.
[0053] The pressure balance model setting unit 25 incorporates pressure models such as pressure characteristics within the turbine related to the measured variables, pressure loss calculation formulas for piping and equipment, and pressure loss calculation formulas associated with the opening degree of the control valve as constraint conditions 13 into the true value estimation unit 10. 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 within the turbine, the pressure loss calculation formula for piping and equipment, and the pressure loss calculation formula associated with the opening degree of the control valve, based on the measured values acquired by the measured value input unit 21, and calculates a value corresponding to the measured variable 11, which is then used as the new measured value for the measured variable 11. This makes it possible to add redundancy to the measurement variable 11, which previously lacked redundancy, or to increase its redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10. [Examples]
[0055] Next, we will describe another configuration of the plant instrumentation device 1 that improves the accuracy of the estimated true value yi. Figure 7 is a diagram showing the configuration of an equipment deterioration monitoring system equipped with the plant instrumentation device 1 of the embodiment.
[0056] The plant instrumentation system 1 in Figure 7 is constructed by adding a statistical model setting unit 26 to the plant instrumentation system 1 described in Figure 2. Other components are the same as in Figure 2, so their explanation is omitted here. Alternatively, the plant instrumentation system 1 in Figure 4 may be constructed by adding a statistical model setting unit 26.
[0057] The statistical model setting unit 26 sets a statistical model represented by relational expressions of instrument measurement variables obtained based on measured values of the plant's normal operation data, and incorporates the relational expressions of the statistical model as constraint conditions 13 into the true value estimation unit 10. 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 represented by a relational expression for the instrument's measured variables, which is derived from the measured values of the plant's normal operation data. The statistical model calculates a value corresponding to the measured variable 11, and this value becomes the new measured value for the measured variable 11. This makes it possible to add redundancy to the non-redundant measured variable 11, or to increase its 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 unit 26 may take in 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 statistical model.
[0060] The equipment degradation judgment 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 degradation variables to evaluate the degradation of the equipment. [Examples]
[0061] Next, we will describe another configuration of the plant instrumentation device 1 that improves the accuracy of the estimated true value yi. Figure 8 is a diagram showing the configuration of an equipment deterioration monitoring system equipped with the plant instrumentation device 1 of the embodiment.
[0062] The plant instrumentation system 1 in Figure 8 is constructed by adding a simulator setting unit 27 to the plant instrumentation system 1 described in Figure 2. Other components are the same as in Figure 2, so their explanation is omitted here. Alternatively, the plant instrumentation system 1 in Figure 4 may be constructed by adding a simulator setting unit 27.
[0063] The simulator setting unit 27 sets up an analysis simulator that simulates plant behavior and incorporates the calculation formula of the analysis simulator as constraint conditions 13 into the true value estimation unit 10. This improves the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.
[0064] Furthermore, the simulator setting unit 27 performs a simulation using the measured values acquired by the measured value input unit 21 to calculate a value corresponding to the measured variable 11, and sets this as the new measured value for the measured variable 11. This makes it possible to add redundancy to the non-redundant measured variable 11, or to increase its redundancy, thereby improving the calculation accuracy of the DR processing unit 14 of the true value estimation unit 10.
[0065] Furthermore, the simulator setting unit 27 may take in 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.
[0066] The equipment degradation judgment device 31 may have a simulator similar to the analysis simulator set by the simulator setting unit 27, and perform simulations using assumed degradation variables to evaluate the degradation of the equipment. [Examples]
[0067] Next, a plant maintenance optimization system equipped with the plant instrumentation device 1 of the embodiment will be described. The plant maintenance optimization system is a system that equalizes the workload of inspecting instruments during periodic maintenance.
[0068] In detail, the plant maintenance optimization system predicts the time it will take to reach the inspection threshold based on the increasing trend of penalty values for individual instruments, evaluates the volume of instrument inspections in subsequent periodic inspections, and provides inspection timings for each instrument to level out the volume of inspections in each periodic inspection. This optimization of maintenance volume prevents increased costs due to increased workload caused by concentrated instrument inspections during certain periodic inspections.
[0069] As shown in Figure 9, if the penalty values for instrument A and instrument B are predicted to reach the threshold at the same time, for example, by inspecting instrument B early, the penalty values for instrument A and instrument B will reach the threshold at different times, thereby preventing a concentration of inspection work on instrument A and instrument B.
[0070] Figure 10 is a diagram showing the configuration of a plant maintenance optimization system equipped with the plant instrumentation device 1 of the embodiment.
[0071] The plant instrumentation system 1 in Figure 10 is constructed by adding the plant thermal balance calculation unit 24 described in Figure 5, the pressure balance model setting unit 25 described in Figure 6, the statistical model setting unit 26 described in Figure 7, and the simulator setting unit 27 described in Figure 8 to the plant instrumentation system 1 described in Figure 4. The configuration of each is the same as described above, so the explanation is omitted here.
[0072] In the plant maintenance optimization system of this embodiment, the plant thermal 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 each of these components may be included.
[0073] The plant maintenance optimization system is equipped with a maintenance volume optimization device 33, which optimizes the maintenance volume based on the output of the equipment deterioration / instrument drift judgment device 32 and the penalty value.
[0074] Next, we will explain how penalty values are handled in the equipment deterioration judgment device 31, the equipment deterioration / instrument drift judgment device 32, and the maintenance volume optimization device 33.
[0075] For monitoring the condition of the equipment degradation judgment device 31 and the equipment degradation / instrument drift judgment device 32, for example, the penalty value threshold is set to 1.96^2. This corresponds to the deviation between the measured value and the estimated true value of the instrument exceeding the 95% confidence interval, assuming that the measurement variability of the instrument is normal, meaning that the instrument contains statistically unacceptable drift error. To detect instrument drift earlier, the penalty value threshold may be set to 1.0^2. This corresponds to the deviation between the measured value and the estimated true value of the instrument exceeding the 68% confidence interval. When the penalty value of each instrument reaches or is expected to reach these thresholds, the system prompts inspection of the instrument.
[0076] Furthermore, in the application of the maintenance volume optimization device 33 for trend monitoring, as shown in Figure 9, the inspection timing for 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 has not reached the threshold, if a clear increasing trend is observed, the system will prompt inspection of the target instrument.
[0077] Furthermore, by predicting inspection timings based on the monitoring results of the maintenance volume optimization device 33 and planning the inspection timings for each instrumentation component to equalize the maintenance volume of instruments during each scheduled inspection, it is possible to suppress increases in maintenance costs and optimize maintenance.
[0078] Furthermore, the present invention is not limited to the embodiments described above, and various modifications are included. The embodiments described above are described in detail for the purpose of clearly illustrating the present invention, and are not necessarily limited to those having all the configurations described. In addition, 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 System 10 True Value Estimation Unit 11 Measurement Variables 12 Virtual Variables 13 Constraints 14 DR Processing Unit 15. Penalty Value Calculation Section 21 Measurement value input section 22 Virtual Variable Setting Section 23 Constraint Setting Section 24 Plant Thermal Balance Calculation Unit 25 Pressure balance model setting section 26 Statistical Model Setting Section 27 Simulator Settings Section 31 Equipment deterioration judgment device 32. Equipment Degradation / Instrument Drift Detection Device 33. Maintenance volume optimization device
Claims
1. A method for monitoring the deterioration of plant equipment, The processing unit of the plant equipment degradation monitoring system used in power plants is The estimated true value of the measured value is calculated from the measured value acquired by the instrument of the power plant, the assumed degradation variable set for the location in the power plant where degradation is expected, and the constraints relating to the measured value and the assumed degradation variable. The estimated true value of the measured value and the penalty value are calculated from the measured value. A method for monitoring the deterioration of plant equipment, characterized by the following features.
2. A plant equipment deterioration monitoring system used in a power plant, A measurement value input unit that inputs measurement values acquired by the instruments of the power plant, A virtual variable setting unit sets assumed degradation variables for locations within the power plant where degradation is expected, A true value estimation unit calculates the estimated true value of the measured value from the measured value, the assumed degradation variable, and the constraints relating to the measured value and the assumed degradation variable. A plant equipment deterioration monitoring system characterized by comprising a penalty value calculation unit that calculates a penalty value from the measured value and the estimated true value of the measured value.