Maintenance plan support system and maintenance plan support method

Abstract

To provide a maintenance plan support system and maintenance plan support method for providing, an overall optimized maintenance plan which uses information at multiple standpoints including, a failure and a deterioration of an object facility, and capable of contributing to improvement of reliability.SOLUTION: A maintenance plan support system comprises: a system monitoring plan part 11 for obtaining, by a simulator using a physical model which indicates behavior of a system of a nuclear power plant, a correlation model which indicates a correlation between, an appliance or gauge of the system and performance of the system; an appliance monitoring plan part 12 for obtaining, by the simulator, a contribution degree to the performance of the system, of the appliance or the gauge of the system, from a performance change ratio of the system; a system monitoring part 13 for obtaining a system monitoring result from monitoring and measurement data of the system, according to the correlation model obtained by the system monitor plan part; an appliance monitor part 14 for obtaining an appliance monitoring result, from the monitoring and measurement data of the system, according to the contribution degree obtained by the appliance monitoring plan part; and a maintenance plan update part 16 for updating the maintenance plan on the basis of the system monitoring result and appliance monitoring result.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a maintenance plan support system and a maintenance plan support method for supporting maintenance activities in a nuclear power plant. [Background technology]

[0002] Nuclear power plants are made up of hundreds of systems and numerous pieces of equipment. In order to maintain safety and maximize the performance of the power plant, maintenance activities are carried out to maintain and improve its reliability.

[0003] Meanwhile, as disclosed in Patent Document 1, the simulation technology for nuclear power plants has improved, and there is a technology in which abnormal events are simulated by a nuclear power plant simulator, various operating parameters are collected as learning data, and a diagnostic model for the nuclear power plant is generated. In detail, Patent Document 1 discloses that an abnormal event is detected and the type is identified by using an AI that has learned the relationship between the parameters that reproduce the abnormal event by the simulator and the abnormal event. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-020555 Summary of the Invention [Problem to be solved by the invention]

[0005] In maintenance activities at nuclear power plants, it is desirable to establish a comprehensive optimization of maintenance processes that take into account monitoring and risk assessment, such as ensuring sufficient performance of systems and equipment and dealing with any abnormal trends that may occur.

[0006] An object of the present invention is to provide a maintenance support system and a maintenance support method that can provide an optimized maintenance plan using information from multiple perspectives, including the status of malfunctions and deterioration of the target equipment, and contribute to improving reliability. [Means for solving the problem]

[0007] In order to solve the above problems, the maintenance planning support system for a nuclear power plant of the present invention comprises a system monitoring planning unit that uses a simulator using a physical model that shows the behavior of the system of the nuclear power plant to determine a correlation model that shows the correlation between equipment or instruments of the system and the performance of the system, an equipment monitoring planning unit that uses the simulator to determine the contribution of the equipment or instruments of the system to the performance of the system from the performance change rate of the system, a system monitoring unit that determines system monitoring results from monitoring and measurement data of the system in accordance with the correlation model determined by the system monitoring planning unit, an equipment monitoring unit that determines equipment monitoring results from the monitoring and measurement data of the system in accordance with the contribution determined by the equipment monitoring planning unit, and a maintenance plan update unit that updates a maintenance plan based on the system monitoring results and the equipment monitoring results. Effect of the Invention

[0008] According to the present invention, for the maintenance of a nuclear power plant, an optimized maintenance plan can be provided by using information from multiple perspectives, including the state of malfunctions and deterioration of the target equipment, thereby contributing to improving reliability. [Brief description of the drawings]

[0009] [Figure 1] FIG. 2 is a schematic diagram illustrating functions of the maintenance planning support system according to the present embodiment. [Diagram 2] FIG. 2 is a block diagram showing a configuration of a system monitoring planning unit. [Diagram 3] FIG. 2 is a block diagram showing a configuration of an analysis unit. [Figure 4] FIG. 2 is a block diagram for explaining details of a physical model of an analysis unit. [Diagram 5] FIG. 2 is a diagram illustrating an example of a system configuration represented by a physical model. [Figure 6] FIG. 11 is a diagram for explaining the processing contents of a correlation calculation unit. [Figure 7] 2 is a block diagram showing a configuration of an equipment monitoring plan unit. FIG. [Figure 8] 11 is a diagram for explaining the processing contents of a contribution degree calculation unit. FIG. [Figure 9] FIG. 2 is a block diagram showing a configuration of a system monitoring unit. [Figure 10A] FIG. 13 is a diagram showing the trend of the correlation output F1. [Figure 10B] 1 is a diagram showing how correlation output F1(t) at time t is converted into performance X(t) according to a relational expression showing the relationship between correlation output F1 and performance X. FIG. [Figure 10C] FIG. 13 is a diagram showing a time trend of performance X. [Figure 11] 2 is a block diagram showing a configuration of a device monitoring unit; FIG. [Figure 12A] FIG. 13 is a diagram showing time trends of the performance X of a system of interest and the correlation output F1. [Figure 12B] FIG. 13 is a diagram showing the time trends of output a (measurement), output b (measurement), and output c (measurement) of device A with a high degree of contribution. [Figure 13] FIG. 13 is a diagram illustrating an example of a disturbance input to a physical model. [Figure 14A] FIG. 13 is a diagram showing the relationship between the output a' (virtual) and the performance X' (virtual) when all disturbances are input. [Figure 14B] FIG. 13 is a diagram showing the rate of change of performance X' (hypothetical) with respect to disturbance α (hypothetical) when a specific parameter is changed. [Figure 14C] FIG. 13 is a diagram showing the rates of change of outputs a' (virtual) to e' (virtual) with respect to a disturbance α (virtual) when a particular pattern of disturbance is changed. [Figure 15] FIG. 2 is a block diagram illustrating a specific configuration of the maintenance plan support system. [Figure 16] FIG. 11 is a diagram illustrating an example of configuration data of a configuration management DB. [Figure 17] FIG. 11 is a diagram showing an example of configuration data of a measurement item DB. [Figure 18]FIG. 13 is a diagram showing an example of configuration data of a monitoring and measurement data DB. [Figure 19A] FIG. 13 is a diagram for explaining an example of a method for utilizing the system monitoring results (trends). [Figure 19B] FIG. 13 is a diagram for explaining another example of a method for utilizing the system monitoring results (trends). [Figure 20] FIG. 2 is a flow diagram illustrating an operation of the maintenance plan support system according to the embodiment. [Figure 21] FIG. 13 is a diagram showing the processing contents of a comprehensive judgment. [Figure 22A] FIG. 13 is a diagram showing maintenance plan information before updating. [Figure 22B] FIG. 13 is a diagram showing updated maintenance plan information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. The maintenance plan support system of this embodiment performs a correlation detection process (first procedure) in which a simulator is used to use a physical model defined from the component equipment and instruments of a nuclear power plant system and indicates the behavior of the system, and a simulation is performed using multiple changes in the system's operating state and state changes due to the natural environment and performance changes of the equipment and instruments as input conditions to evaluate the performance defined for the system, and extracts equipment or instruments that have a high correlation with the performance, thereby extracting governing factors of the system performance, and a contribution evaluation process (second procedure) in which a simulation is performed using performance changes of a specific equipment or instrument among the component equipment and instruments of the system as input conditions to evaluate the performance defined for the system, and evaluates the contribution of the equipment or instrument to the performance of the system from the rate of change in performance of the system, and monitors the equipment or instruments that have a high correlation with the plant performance extracted in the correlation detection process among the component equipment and instruments included in the system, and extracts equipment or instruments that should be maintained with priority based on the contribution determined in the contribution evaluation process, thereby updating the maintenance plan.

[0011] FIG. 1 is a schematic diagram for explaining the functions of the maintenance plan support system of this embodiment. The maintenance planning support system includes a system monitoring planning unit 11 that performs correlation detection processing to extract governing factors of system performance by evaluating performance defined for the system and extracting equipment or instruments that are highly correlated with the performance, thereby generating a correlation model, and an equipment monitoring planning unit 12 that performs contribution evaluation processing to evaluate the contribution of the equipment or instrument to the performance of the system from the rate of change of system performance, thereby generating a contribution.

[0012] In detail, the system monitoring planning unit 11 and the equipment monitoring planning unit 12 use physical models (physical model N, physical model D, ...) that indicate the behavior of multiple systems defined by the configuration management DB (210) and the measurement item DB (230) to perform simulations using multiple changes in the operating state of the system, changes in the state due to the natural environment, and changes in the performance of the equipment and meters as input conditions, to evaluate the performance defined for the system and generate a correlation model and a contribution degree.

[0013] The system monitoring unit 13 analyzes information in a monitoring and measurement data DB (240) that stores data measured on the equipment (systems and devices) to be maintained, according to a correlation model, and outputs a system monitoring result (trend) that indicates the time fluctuation of the system performance.

[0014] The equipment monitoring unit 14 analyzes information in a monitoring and measurement data DB (240) that stores measured data of the equipment (systems and equipment) to be maintained, according to the degree of contribution, and outputs equipment monitoring results (trends) that indicate the time fluctuations of the output of equipment or meters with high contribution degrees.

[0015] The maintenance plan update unit 16 evaluates the system monitoring results and the equipment monitoring results, and updates the maintenance plan information according to a combination of whether or not there is a trend for deterioration in system performance and whether or not there is a trend for deterioration in equipment performance. The following describes in detail the functions and operations of the maintenance planning support system.

[0016] FIG. 2 is a block diagram showing the configuration of the system monitoring planning unit 11. As shown in FIG. The system monitoring planning unit 11 includes an analysis unit 111 and a correlation calculation unit 112 .

[0017] The analysis unit 111 is composed of physical models that indicate multiple system behaviors, which will be described in detail later, and inputs disturbance information (disturbance α (virtual), disturbance β (virtual), disturbance γ (virtual), disturbance δ (virtual) ..., disturbance ω (virtual)) that indicates changes in the system's operating state and state due to the natural environment and changes in the performance of the equipment and instruments, and outputs system performance information (performance X' (virtual), performance Y' (virtual), performance Z' (virtual), ...) and system output information (output a' (virtual), output b' (virtual), output c' (virtual), output d' (virtual), output e' (virtual), ...).

[0018] Here, disturbance refers to a parameter that indicates a decrease in the performance of the equipment and instruments that make up the system, such as a pipe leak, a decrease in pump performance, a blockage in a heat exchanger, or a drift in a pressure gauge in a cooling system. It can also include a parameter that indicates a change in the environment including the system, such as an increase in seawater temperature that deteriorates the cooling performance in a cooling system. In addition, in the specification, when indicating information in a simulation, it is written as (virtual), and when indicating information in an actual device, it is written as (measured).

[0019] The correlation calculation unit 112, which will be described in detail later with reference to Figure 6, extracts the governing factors of system performance by extracting devices or instruments that are highly correlated with performance, and outputs them as correlation output information (correlation output F1', correlation output F2', correlation output F3', ...) and a correlation model.

[0020] FIG. 3 is a block diagram showing the configuration of the analysis unit 111. As shown in FIG. The analysis unit 111 has physical models of multiple systems, such as a physical model of system behavior in a normal operation mode (physical model N), a physical model of system behavior in an operation mode when a specified fault occurs, and a physical model of system behavior in an operation mode when an accident occurs (physical model D), and outputs correlation output information and a correlation model based on each physical model.

[0021] The input parameter switching unit switches the disturbance information to be input in accordance with the physical model to be analyzed. The output parameter processing unit is a processing unit that distributes the analysis result into system performance information and system output information according to the analyzed physical model.

[0022] FIG. 4 is a block diagram for explaining the details of the physical model of the analysis unit 111. As shown in FIG. The physical model is a system behavior model defined by the system equipment configuration, system instrument configuration, and system and equipment requirements stored in the configuration management DB (210) and the output list (measurement items) stored in the measurement item DB (230).

[0023] Here, the configuration information of a system is information including devices such as valves, pumps, motors, strainers, and blowers that configure the system, and their locations. The configuration information of a system is information including instruments such as thermometers, flow meters, and pressure gauges of the systems that make up the system and their arrangement. System and equipment requirements refer to the functional and performance requirements of the system, as well as the design requirements for the equipment that makes up the system, and are information that includes the functions and performance required of the system and the equipment that makes up the system, mainly for safety reasons.

[0024] The output list (measurement) is the items measured by instruments, sensors, etc. in the system. Most of these are input into the process computer (also called a procon), but some also include information from instruments installed on-site that are not input into the process computer, and from automatic or manual measuring instruments such as temperature and vibration sensors for status monitoring.

[0025] FIG. 5 is a diagram illustrating an example of a system configuration represented by a physical model. 5 shows the system configuration of a reactor auxiliary cooling system / auxiliary cooling seawater system, with the system configuration stored in the configuration management DB (210) and detailed information on pressure P, temperature T, differential pressure DP, and flow rate F stored in the measurement item DB (230). The physical model defines a system behavior model based on the configuration management DB (210) and the measurement item DB (230).

[0026] Next, the processing contents of the correlation calculation unit 112 (see FIG. 2) of the system monitoring planning unit 11 will be explained with reference to FIG. FIG. 6 shows a case where the correlation calculation unit 112 calculates output information (output a' (virtual), output b' (virtual), output c' (virtual)) of a system having a high correlation with performance X' (virtual).

[0027] The graph on the left side of Figure 6 shows the relationship between each of the system's output a' (virtual), output b' (virtual), ..., output e' (virtual) and performance X' (virtual). As the graph shows, each of the output a' (virtual), output b' (virtual), ..., output e' (virtual) is a factor of performance X' (virtual), but there is no correlation between them and performance X' (virtual).

[0028] However, when a correlation function F1'(a', b', c') is introduced with variables being output a'(virtual), output b'(virtual), and output c'(virtual) selected from output a'(virtual), output b'(virtual), ..., output e'(virtual) of the system, the performance X'(virtual) and the correlation function F1'(a', b', c') have a correlation represented by a predetermined relational expression (correlation expression), as shown in the graph on the right side of the page in Fig. 6. Hereinafter, in this specification, the correlation function F1'(a', b', c') will be referred to as correlation output F1'(a', b', c').

[0029] As described above, the correlation calculation unit 112 obtains correlation output information (correlation output F1', correlation output F2', correlation output F3', ...) regarding the system output information (output a' (virtual), output b' (virtual), output c' (virtual), output d' (virtual), output e' (virtual), ...) for each of the system performance information (performance X' (virtual), performance Y' (virtual), performance Z' (virtual), ...). Then, the correlation calculation unit 112 outputs the system performance information, correlation output information, and correlation equation as a correlation model.

[0030] Although details will be described later, the system monitoring unit 13 calculates system performance information based on the above correlation model from the system output data in the monitoring and measurement data DB (240) to obtain system inspection results (trends).

[0031] Next, the equipment monitoring plan unit 12 will be described with reference to FIG. 7 and FIG. FIG. 7 is a block diagram showing the configuration of the equipment monitoring planning unit 12. As shown in FIG. The equipment monitoring plan unit 12 includes an analysis unit 121 and a contribution degree calculation unit 122 . The analysis unit 121 is the same as the analysis unit 111 (see FIG. 2) of the system monitoring planning unit 11, and therefore a description thereof will be omitted.

[0032] The contribution calculation unit 122, which will be described in detail later with reference to FIG. 8, refers to the correlation model and the arrangement table of disturbances and disturbance targets output by the correlation calculation unit 112, and determines the contribution to each piece of performance information from the system performance information (performance X' (virtual), performance Y' (virtual), performance Z' (virtual), ...) output by the analysis unit 121 and the system output information (output a' (virtual), output b' (virtual), output c' (virtual), output d' (virtual), output e' (virtual), ...).

[0033] Furthermore, since the impact of performance information (performance X' (virtual), performance Y' (virtual), performance Z' (virtual), ...) on a system due to a change in performance of an equipment is often small, it is assumed that it is difficult to grasp the impact of a specific disturbance from a change in performance information or a change in correlation output information (correlation output F1', correlation output F2', correlation output F3', ...), and therefore the contribution calculation unit 122 has a function to output an output (selected from outputs a' to e') that is highly sensitive to the impact of a change in performance of the equipment.

[0034] FIG. 8 is a diagram for explaining the processing contents of the contribution degree calculation unit 122. As shown in FIG. The graph on the left side of Figure 8 shows the effect of the performance degradation (= disturbance) of the equipment on the performance information (performance X' (virtual), ...) of the system. In more detail, it shows the rate of change of performance X' (virtual) with respect to the changes of disturbance α (virtual), disturbance β (virtual), and disturbance γ (virtual).

[0035] When the rate of change in performance changes in response to a change in disturbance, the contribution calculation unit 122 determines that the influence (contribution) of the disturbance on the change in performance is large. The contribution calculation unit 122 determines the influence (contribution) of the disturbance into multiple stages, "High", "Middle", and "Low", depending on the magnitude of the rate of change in performance in response to the change in disturbance.

[0036] Here, the contribution calculation unit 122 can determine the correspondence between the disturbance and the performance of the equipment or instrument based on the "table of disturbances and disturbance targets" which shows the correspondence between the disturbance parameters and disturbance targets, so that a disturbance which is determined to have a large influence (contribution) on the change in performance can be rephrased in terms of the performance of the equipment or instrument.

[0037] In addition, in Fig. 8, the vertical axis of the graph is the performance X' (virtual), but the correlation output F1', which is known to have a correlation with the performance X' (virtual), may be used instead. In other words, the vertical axis of the three graphs on the left side of the page in Fig. 8 may be either the performance X' (virtual) or the correlation output F1'.

[0038] The contribution calculation unit 122 obtains the contribution calculation result of each disturbance (performance of equipment or instrument) to the performance X' (virtual) by referring to the correlation model and the "table of disturbances and disturbance targets" shown in the table on the lower right side of Fig. 8. The contribution calculation result is obtained for each piece of performance information (performance X' (virtual), performance Y' (virtual), performance Z' (virtual), ...).

[0039] Next, the system monitoring unit 13 will be described with reference to FIG. 9 and FIG. FIG. 9 is a block diagram showing the configuration of the system monitoring unit 13. As shown in FIG. The system monitoring unit 13 is composed of a parameter conversion unit, a correlation processing unit, and an output unit.

[0040] The system monitoring unit 13 analyzes the measurement data of a monitoring and measurement data DB (240) that stores system measurement data measured at predetermined times or at predetermined intervals, which is either input into a process computer of the nuclear power plant or obtained by field instruments, based on the correlation model generated by the system monitoring planning unit 11, and outputs a system monitoring result (trend) that indicates the time fluctuation of the system performance.

[0041] In detail, the parameter conversion unit converts the measurement data (output a (measurement), output b (measurement), output c (measurement), output d (measurement), output e (measurement), ...) in the monitoring / measurement data DB (240) into correlation output information (correlation output F1, correlation output F2, correlation output F3, ...) based on the correlation model.

[0042] The correlation processing unit performs processing to convert the correlation output information (correlation output F1, correlation output F2, correlation output F3, ...) output by the parameter conversion unit into performance information (performance X (measurement), performance Y (measurement), performance Z (measurement), ...) based on a correlation equation that indicates the relationship between the performance information of the correlation model and the correlation output information.

[0043] The output unit notifies the maintenance plan update unit 16 of the time trend of the correlation output information (correlation output F1, correlation output F2, correlation output F3, ...) or the time trend of the performance information (performance X (measurement), performance Y (measurement), performance Z (measurement), ...).

[0044] Here, the time trend of the correlation output information of the parameter conversion unit and the time trend of the performance information of the correlation processing unit will be described with reference to Figs. 10A, 10B, and 10C. FIG. 10A is a diagram showing a time trend of the correlation output F1 outputted by the parameter conversion unit up to time t.

[0045] 10B is a diagram explaining the process of converting correlation output information (correlation output F1, correlation output F2, correlation output F3, ...) into performance information (performance X (measurement), performance Y (measurement), performance Z (measurement), ...) in the correlation processing unit. It shows how correlation output F1(t) at time t is converted into performance X(t) according to a relational expression showing the relationship between correlation output F1 and performance X.

[0046] FIG. 10C is a diagram showing the time trend of the performance X obtained by converting the time trend of the correlation output F1 in FIG. 10A into the performance X in FIG. 10B.

[0047] 10C, control value 1 is, for example, a design requirement value, and exceeding this value is a regulatory constraint. Control value 2 is, for example, a control value that, when exceeded, triggers a maintenance action (for example, increasing the frequency of monitoring or performing an overhaul at the next regular inspection).

[0048] Next, the device monitoring unit 14 will be described with reference to FIG. 11, FIG. 12A, and FIG. 12B. FIG. 11 is a block diagram showing the configuration of the device monitoring unit 14. As shown in FIG. The device monitoring unit 14 is composed of a parameter selection unit and an output unit.

[0049] The equipment monitoring unit 14 analyzes the measurement data of the monitoring and measurement data DB (240) that stores the system measurement data measured at a predetermined time or at a predetermined interval, which is taken into the process computer of the nuclear power plant or obtained by the field instruments, based on the contribution generated by the equipment monitoring planning unit 12, and outputs the equipment monitoring result (trend) that shows the time fluctuation of the performance of the equipment. In other words, it monitors the output that is highly sensitive to the change in the performance of the equipment, and outputs it as a time trend.

[0050] In detail, the parameter selection unit selects, as a monitoring parameter for the equipment performance, an output (measurement) that is highly sensitive to the performance change of the equipment that is highly sensitive to the performance X (measurement) (or the correlation output F1 that is correlated with the performance X) among the equipment that constitutes the system, that is, for the equipment with a high contribution degree. The figure shows the case where the correlation output F1, output a (measurement), output b (measurement), and output c (measurement) are selected.

[0051] The output unit outputs the time variation of the output (measurement) that is highly sensitive to the performance change of the equipment selected by the parameter selection unit as the equipment monitoring result (trend).

[0052] An example of the device monitoring result obtained by the device monitoring unit 14 will be described with reference to FIGS. 12A and 12B. FIG. 12A is a diagram showing a time trend (system monitoring result) of the performance X of a system of interest and the correlation output F1 output by the system monitoring unit 13. FIG. 12B is a diagram showing time trends of output a (measurement), output b (measurement), and output c (measurement) (device monitoring results) for device A with a high degree of contribution.

[0053] In Fig. 12A, the performance X and correlation output F1 have not changed as a result of monitoring the equipment, and therefore it can be seen that there is no abnormality in the system performance. On the other hand, the change in the performance of the equipment before a major change in the system performance appears is monitored by the output a (measurement), output b (measurement), and output c (measurement) in Fig. 12B.

[0054] In Fig. 12B, since the output a (measurement) shows a tendency of change over time, it is possible to extract disturbances (= performance changes of equipment A) that are highly sensitive to the output a (measurement). Therefore, as a maintenance decision, for example, a maintenance plan can be made to carry out an overhaul inspection of equipment A during regular inspections or to increase the frequency of monitoring during operation.

[0055] The maintenance planning support system of this embodiment will be described in more detail below. FIG. 13 is a diagram showing an example of settings of disturbances to be input to a physical model. For each type of disturbance (disturbance parameter), the disturbance target such as equipment or environment, the range of the disturbance (for example, min-max), all patterns of how the disturbance is applied, and a specific pattern of how the disturbance is applied are set.

[0056] Here, the designation of all patterns of how to apply a disturbance is a designation of a disturbance to be input to the analysis unit 111 of the system monitoring planning unit 11, and all patterns are set. The designation of a specific pattern of how to apply a disturbance is a designation of a disturbance to be input to the analysis unit 121 of the equipment monitoring planning unit 12, and is set when calculating the contribution of an equipment or instrument.

[0057] Next, an example of the analysis result according to the application of all patterns or a specific pattern of disturbance will be described with reference to Figs. 14A, 14B, and 14C.

[0058] Fig. 14A is a diagram showing the relationship between the output a' (virtual) and the performance X' (virtual) when all patterns of disturbance are input. In Fig. 14A, the correlation between the output a' (virtual) and the performance X' (virtual) cannot be found, but it is possible that a correlation can be found.

[0059] Fig. 14B is a diagram showing the rate of change of performance X' (virtual) with respect to disturbance α (virtual) when a specific pattern of disturbance is changed. Fig. 14B is an example showing that it is difficult to grasp the influence of a specific disturbance from the change in performance X' (virtual). Also, in Fig. 14B, it can be said that the change in performance of the equipment constituting the system is too small to attempt to grasp it as an influence change of performance X' (virtual) due to a specific disturbance.

[0060] Fig. 14C is a diagram showing the rate of change of output a' (virtual) to output e' (virtual) with respect to disturbance α (virtual) when a specific pattern of disturbance is changed. Fig. 14C is another example of analysis results in a case where it is difficult to grasp the influence of a specific disturbance from the change in performance X' (virtual) as in Fig. 14B. In Fig. 14C, it can be evaluated that output a' (virtual) and output e' (virtual) have relatively high sensitivity to disturbance (=performance change).

[0061] Next, a specific configuration of the maintenance plan support system according to the embodiment will be described with reference to the block diagram of FIG. The maintenance plan support system 300 includes a maintenance plan support device 100 and a database device 200 that is an external storage device.

[0062] The maintenance plan support device 100 includes a processing unit 10, a storage unit 20, an input unit 30, an output unit 40, and a communication unit 50. The processing unit 10 includes a system monitoring plan unit 11, an equipment monitoring plan unit 12, a system monitoring unit 13, an equipment monitoring unit 14, and a maintenance plan update unit 16, which are shown in FIG.

[0063] The memory unit 20 stores the system equipment configuration 21, the system instrument configuration 22, monitoring item extraction information 23 indicating the quantities measured in the system, a performance list 24 indicating the system performance indexes, operating conditions 25 such as during normal times and accidents, and environmental conditions 26 such as seawater temperature and air temperature.

[0064] The processing unit 10 includes a CPU (Central Processing Unit), and the CPU executes various programs stored in the RAM, HDD, etc. of the processing unit 10 to realize the functions of a system monitoring planning unit 11, an equipment monitoring planning unit 12, a system monitoring unit 13, an equipment monitoring unit 14, and a maintenance plan update unit 16.

[0065] The memory unit 20 is a HDD and stores various data for the maintenance plan support device 100 to execute processing. The input unit 30 is a device for inputting instructions to a computer, such as a keyboard or a mouse, and inputs instructions such as to start a program. The output unit 40 is a display or the like, and displays the execution status and execution results of processing by the maintenance plan support device 100. The communication unit 50 exchanges various data and commands with other devices via the network NW.

[0066] The database device 200 includes a configuration management DB (210), a measurement item DB (230), a monitoring and measurement data DB (240), and the like, which will be described later.

[0067] FIG. 16 shows an example of configuration data in the configuration management DB (210). The configuration management DB 210 is a database that is composed of design requirements, design documents, and actual data for the power plant. For systems and equipment (collectively referred to as "facilities") that are the subject of maintenance, the equipment that is the subject of maintenance activities such as inspection, testing, monitoring, and repair, and the timing (cycle) of carrying out such activities are determined for the more important facilities in terms of maintaining and improving safety, in order to maintain the required specifications and functions. When changing the inspection cycle of a certain facility, as in this embodiment, the change must be made within a range that complies with laws and regulations, in principle. For example, the regulations may require a certain percentage of non-destructive testing within a certain number of years, such as 10 years.

[0068] FIG. 17 shows an example of data constituting the measurement item DB (230). The measurement item DB (230) stores information on the measurement items being performed in the facility (system or device) to be maintained, the measurement accuracy for each measurement item, the storage location of the measurement data, and the like. Furthermore, the measurement item DB (230) stores information on virtual measurement items referenced by the analysis units 111 and 121 configured using physical models.

[0069] FIG. 18 shows an example of data constituting the monitoring and measurement data DB (240). The monitoring and measurement data DB (240) stores, as measurement log data, the date and time when data was actually measured and the value of the data for the measurement items stored in the measurement item DB (230) and virtual measurement items.

[0070] Next, a method of utilizing the system monitoring results (trends) will be described with reference to Figs. 19A and 19B. In the utilization method shown in FIG. 19A, when a change over time in performance X is estimated in the time trend of performance X described in FIGS. 10A to 10C, an estimated trend line is obtained, and the time at which the maintenance threshold is reached is set as the recommended timing for the next maintenance.

[0071] FIG. 19B is a diagram showing a method for determining the recommended timing for the next maintenance from the system monitoring results (trends) obtained using a plurality of physical models. In detail, the time trend of performance X is found based on the correlation model found for each of multiple physical models (for example, physical model N and physical model D), and then an estimated trend line is found from each time trend. The shortest arrival time of the estimated lines that reach the maintenance threshold is set as the recommended timing for the next maintenance. This makes it possible to prevent unexpected performance degradation and improve the reliability of maintenance.

[0072] Next, the operation of the maintenance plan support system according to the embodiment will be described with reference to the flow chart of FIG.

[0073] In step S1, the maintenance planning support system prepares a simulator using a physical model including components and instruments.

[0074] In step S2, the maintenance planning support system (system monitoring and planning unit 11) performs analysis using a simulator using a combination of multiple disturbances (changes in conditions due to operating conditions and the natural environment, and changes in the performance of equipment and instruments that make up the system) as input conditions.

[0075] In step S3, the maintenance plan support system (system monitoring and planning unit 11) evaluates the system performance, parameters highly correlated with the performance (combined calculation of outputs measured in the plant), and the correlation between the two.

[0076] In step S4, the maintenance planning support system (system monitoring unit 13) monitors the system using parameters that are highly correlated with performance.

[0077] In step S5, the maintenance planning support system (equipment monitoring planning unit 12) performs analysis using a simulator with reference to the correlation information obtained in step S3, using a specific disturbance (a change in the performance of equipment or instruments that make up the system) as an input condition.

[0078] In step S6, the maintenance planning support system (equipment monitoring planning unit 12) evaluates the contribution of the equipment or instrument to the performance of the system from the sensitivity of the performance change of the equipment or instrument that constitutes the system to the performance of the system.

[0079] In step S7, the maintenance planning support system (device monitoring unit 14) monitors devices or instruments that contribute greatly to performance.

[0080] In step S8, the maintenance plan support system (maintenance plan update unit 16) makes a comprehensive judgment based on the system monitoring results and equipment monitoring results, depending on whether or not there is a tendency for performance degradation in the system performance and the equipment / instrument performance, in accordance with the processing content of the comprehensive judgment in Figure 21.

[0081] In step S9, the maintenance plan support system (maintenance plan update unit 16) updates the maintenance plan.

[0082] For example, the maintenance plan update unit 16 updates the pre-update maintenance plan information shown in Fig. 22A to the pre-update maintenance plan information shown in Fig. 22B. Specifically, the maintenance work of disassembling and inspecting pumps is updated from a plan to perform two pumps in the N+2th time to a plan to perform one pump in the N+1th time and one pump in the N+2th time.

[0083] The maintenance planning support method of this embodiment described above has the following features. For nuclear power plant systems, a first step of evaluating main performance defined for the system through multiple analyses using a simulator that uses a physical model including the system's constituent devices and instruments, with a combination of multiple disturbances, such as changes in the system's operating conditions and natural environment, and changes in the performance of the devices and instruments, as input conditions, and extracting combinations of input conditions that are highly correlated with the main performance, thereby extracting governing factors of the main performance of the system; a second step of evaluating a main performance of the system by performing multiple analyses using the simulator while providing a specific disturbance related to a performance change of a single device or instrument among the components and instruments of the system as an input condition, and evaluating the contribution of the components or instruments of the system to the main performance from the change in the main performance of the system; By performing the procedure in this order, the parameters to be monitored are set as governing factors for the main performance required for the safe operation of the plant, and among the component devices and instruments included in the system, the equipment and instruments that should be maintained or calibrated as a priority are extracted based on their degree of contribution, thereby providing a method for optimizing maintenance while ensuring safe operation.

[0084] The system also has a plurality of physical models that show system behaviors corresponding to a plurality of operation modes, such as a normal operation mode of the nuclear power plant, an operation mode when a predetermined fault occurs, and an operation mode when an accident occurs, The recommended timing for the next maintenance is determined from the time at which an estimated value of the performance trend, obtained based on a simulation using each physical model, reaches a predetermined maintenance threshold value.

[0085] The present invention is not limited to the above-mentioned examples, and various modified examples are included. The above-mentioned examples are described in detail to clearly explain the present invention, and are not necessarily limited to those having all of 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]

[0086] 11 System Monitoring Planning Department 12 Equipment Monitoring Planning Department 13 Grid monitoring section 14 Equipment monitoring department 16 Maintenance Plan Update Division 100 Maintenance planning support device 210 Configuration management DB 230 Measurement item DB 240 Monitoring and measurement data DB 300 Maintenance Planning Support System

Claims

1. A maintenance planning support system for a nuclear power plant, comprising: a system monitoring planning unit that obtains a correlation model that indicates a correlation between an instrument or a gauge of the system and a performance of the system by using a simulator that uses a physical model that indicates a behavior of the system of the nuclear power plant; an equipment monitoring planning unit that determines a contribution of a device or instrument of the system to the performance of the system from a performance change rate of the system using the simulator; a system monitoring unit that determines a system monitoring result from the monitoring and measurement data of the system according to the correlation model determined by the system monitoring planning unit; an equipment monitoring unit that determines an equipment monitoring result from the monitoring and measurement data of the system according to the contribution degree determined by the equipment monitoring planning unit; a maintenance plan update unit that updates a maintenance plan based on the system monitoring result and the equipment monitoring result; A maintenance planning support system equipped with:

2. 2. The maintenance planning support system according to claim 1, the equipment monitoring planning unit determines the degree of contribution by referring to the correlation model determined by the system monitoring planning unit; Maintenance planning support system.

3. 2. The maintenance planning support system according to claim 1, The maintenance plan update unit updates the maintenance plan according to a combination of whether or not there is a trend of deterioration in system performance in the system monitoring result and whether or not there is a trend of deterioration in performance of the equipment in the equipment monitoring result. Maintenance planning support system.

4. 2. The maintenance planning support system according to claim 1, The simulator has a plurality of physical models each having a different state of the system, the system monitoring planning unit obtains the correlation model for each physical model by a simulator; the equipment monitoring planning unit determines the degree of contribution for each physical model using a simulator; the system monitoring unit obtains a system monitoring result for each of the correlation models obtained by using simulators of different physical models; the equipment monitoring unit obtains an equipment monitoring result for each of the contribution degrees obtained by using simulators of different physical models; Maintenance planning support system.

5. 5. The maintenance planning support system according to claim 4, the maintenance plan update unit obtains an estimate of a trend of the system monitoring result or the equipment monitoring result for each of the simulators of the different physical models, and determines the shortest arrival time at which the estimate reaches a maintenance threshold as the recommended timing for the next maintenance. Maintenance planning support system.

6. A maintenance planning support system for a nuclear power plant, comprising: A simulation is performed using a simulator that uses a physical model that is defined from the components and instruments of the nuclear power plant system and indicates the behavior of the system, with a plurality of changes in the operating state of the system and changes in the state due to the natural environment and changes in the performance of the equipment and instruments as input conditions, to evaluate the performance defined for the system, and a correlation detection process is performed to extract the governing factors of the system performance by extracting the equipment or instruments that are highly correlated with the performance; A simulation is performed using a performance change of a specific device or instrument among the components and instruments of the system as an input condition to evaluate the performance defined for the system, and a contribution evaluation process is performed to obtain a contribution to the performance of the device or instrument from a performance change rate of the system; Among the constituent devices and instruments included in the system, devices or instruments having a high correlation with the plant performance extracted in the correlation detection process are monitored, and devices or instruments to be maintained with priority are extracted based on the contribution degree obtained in the contribution degree evaluation process, and a maintenance plan is updated. Maintenance planning support system.

7. A maintenance plan support method for a maintenance plan support system of a nuclear power plant, comprising: A step of obtaining a correlation model showing a correlation between an instrument or a gauge of the system and a performance of the system by a simulator using a physical model showing a behavior of the system of the nuclear power plant; determining a contribution of a device or instrument of the system to the performance of the system from a performance change rate of the system by the simulator; determining a system monitoring result from the system monitoring and measurement data according to the correlation model; determining an equipment monitoring result from monitoring and measurement data of the system according to the contribution degree; updating a maintenance plan based on the system monitoring result and the equipment monitoring result; Conservation planning support methods.

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