Method and device for generating replacement strategy of nuclear power plant equipment

Abstract

The invention provides a replacement strategy generation method and device for nuclear power plant equipment, and relates to the technical field of nuclear power plants. The method comprises the following steps: acquiring historical operation data of nuclear power plant equipment by using a pre-constructed digital twinborn body; determining operation state characteristics of the nuclear power plant equipment and target parameters for reflecting the health condition of the nuclear power plant equipment based on the historical operation data; comparing the target parameter with a preset threshold range of the target parameter, and determining a health assessment index of the equipment; and according to the health assessment index, predicting the probability that the equipment breaks down in the future time period, and then generating an equipment replacement strategy. The historical operation data of the nuclear power plant equipment is used for analyzing the operation state characteristics and the health assessment indexes, the probability of faults in the future time is predicted, a more scientific and reasonable preventive replacement strategy is formulated, the maintenance precision and efficiency of the nuclear power plant equipment are remarkably improved, the risk of non-planned shutdown is reduced, and the maintenance cost is reduced. And the safety and economic benefits of the nuclear power plant are enhanced.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of nuclear power plants, and particularly relates to a method and device for generating a replacement strategy of a nuclear power plant equipment. BACKGROUND

[0002] Nuclear power plants are important energy production facilities, and their safe and stable operation is crucial. In order to ensure that the nuclear power plant equipment can be reliably operated for a long time, effective maintenance strategies need to be taken to prevent equipment failure and reduce unplanned downtime. Traditional equipment maintenance strategies often rely on regular inspections and experience-based judgments, which makes it difficult to accurately predict equipment failure and results in high maintenance costs and low efficiency. Considering the safety and economy of nuclear power plants, how to effectively guide the preventive maintenance and replacement decisions of the equipment is one of the problems to be solved in the field. SUMMARY

[0003] The present disclosure aims to at least partially solve one of the technical problems in the related art.

[0004] To this end, a method for generating a replacement strategy of a nuclear power plant equipment is provided in the first aspect of the present disclosure, comprising:

[0005] obtaining historical operation data of the nuclear power plant equipment by using a pre-constructed digital twin;

[0006] determining an operation state feature of the nuclear power plant equipment based on the historical operation data;

[0007] determining a target parameter for reflecting a health condition of the nuclear power plant equipment according to the operation state feature;

[0008] comparing the target parameter with a preset threshold range of the target parameter, and determining a health evaluation index of the nuclear power plant equipment based on a comparison result;

[0009] predicting a probability of failure of the nuclear power plant equipment in a future time period according to the health evaluation index;

[0010] generating a replacement strategy of the nuclear power plant equipment based on the probability of failure.

[0011] In some embodiments of the present disclosure, the operation state feature of the nuclear power plant equipment is identified based on the historical operation data, comprising: identifying a change trend of the nuclear power plant equipment in the operation process through the historical operation data; and determining the operation state according to the change trend.

[0012] In some embodiments of the present disclosure, the predicting the probability of the nuclear power plant equipment failing in a future time period according to the health assessment index comprises: determining a health state change rule of the nuclear power plant equipment by using the health assessment index; predicting a health trend of the nuclear power plant equipment in the future time period according to the change rule; identifying a plurality of potential failure types of the nuclear power plant equipment and a risk level of each of the potential failure types based on the health trend; and determining the probability of the nuclear power plant equipment failing in the future time period by comprehensively considering the plurality of potential failure types and the risk level of each of the potential failure types.

[0013] In some embodiments of the present disclosure, the digital twin is pre-constructed by the following steps: acquiring design parameters and physical characteristics of the nuclear power plant equipment; creating a three-dimensional virtual model of the nuclear power plant equipment by using the design parameters and the physical characteristics; and combining the three-dimensional virtual model with real-time operation data of the nuclear power plant equipment to establish the digital twin for reflecting the operation condition of the nuclear power plant equipment.

[0014] In some embodiments of the present disclosure, the method further comprises: sending the replacement strategy to a terminal device held by a nuclear power plant execution personnel; acquiring a replacement strategy execution result of the nuclear power plant equipment; and sending the replacement strategy execution result to the digital twin for data synchronization.

[0015] A second aspect of the present disclosure provides a nuclear power plant equipment replacement strategy generation device, comprising:

[0016] The acquisition module is configured to acquire historical operation data of the nuclear power plant equipment by using a pre-constructed digital twin.

[0017] The first determination module is configured to determine an operation state feature of the nuclear power plant equipment based on the historical operation data.

[0018] The second determination module is configured to determine a target parameter for reflecting the health condition of the nuclear power plant equipment according to the operation state feature.

[0019] The third determination module is configured to compare the target parameter with a preset threshold range of the target parameter, and determine a health assessment index of the nuclear power plant equipment based on a comparison result.

[0020] The prediction module is configured to predict a probability of the nuclear power plant equipment failing in a future time period according to the health assessment index.

[0021] The strategy generation module is configured to generate a replacement strategy of the nuclear power plant equipment based on the probability of failing.

[0022] In some embodiments of the present disclosure, the prediction module is specifically configured to: determine a health state change rule of the nuclear power plant equipment by using the health evaluation index; predict a health trend of the nuclear power plant equipment in a future time period according to the change rule; identify a plurality of potential fault types of the nuclear power plant equipment and a risk level of each of the potential fault types based on the health trend; and determine a probability of a fault of the nuclear power plant equipment in the future time period by comprehensively considering the plurality of potential fault types and the risk level of each of the potential fault types.

[0023] In some embodiments of the present disclosure, the device further comprises a construction module; wherein the construction module is configured to: acquire design parameters and physical characteristics of the nuclear power plant equipment; create a three-dimensional virtual model of the nuclear power plant equipment by using the design parameters and the physical characteristics; and combine the three-dimensional virtual model with real-time operation data of the nuclear power plant equipment to establish the digital twin for reflecting the operation condition of the nuclear power plant equipment.

[0024] The third aspect of the present disclosure provides an electronic device, comprising: a processor, and a memory connected with the processor in communication;

[0025] The memory stores computer execution instructions;

[0026] The processor executes the computer execution instructions stored in the memory to implement the method of the first aspect.

[0027] The fourth aspect of the present disclosure provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to implement the method of the first aspect.

[0028] The method for generating a replacement strategy of a nuclear power plant equipment provided by the present disclosure uses historical operation data of the nuclear power plant equipment to analyze its operation state characteristics and health evaluation index, predicts the probability of a fault in a future time, and formulates a more scientific and reasonable preventive replacement strategy, thereby significantly improving the precision and efficiency of maintenance of the nuclear power plant equipment, reducing the risk of unplanned shutdown, and enhancing the safety and economic benefits of the nuclear power plant.

[0029] Additional aspects and advantages of the present disclosure will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0030] The above and / or additional aspects and advantages of the present disclosure will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0031] Figure 1A flowchart of a method for generating a replacement strategy of a nuclear power plant device according to an embodiment of the present disclosure is shown in FIG. 1.

[0032] Figure 2 A schematic diagram of a device for generating a replacement strategy of a nuclear power plant device according to an embodiment of the present disclosure is shown in FIG. 2. DETAILED DESCRIPTION

[0033] Embodiments of the present disclosure are described in detail below with reference to the accompanying drawings, examples of which are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present disclosure, and cannot be understood as a limitation of the present disclosure.

[0034] Specifically, the method and device for generating a replacement strategy of a nuclear power plant device according to an embodiment of the present disclosure are described below with reference to the accompanying drawings.

[0035] Figure 1 A flowchart of a method for generating a replacement strategy of a nuclear power plant device according to an embodiment of the present disclosure is shown in FIG. 1. Figure 1 The method for generating a replacement strategy of a nuclear power plant device can include the following steps:

[0036] Step 101: Obtain the historical operation data of the nuclear power plant device by using a pre-constructed digital twin.

[0037] The digital twin can continuously monitor the state changes of the nuclear power plant device. In some embodiments of the present disclosure, the digital twin can be pre-constructed by the following method: obtaining the design parameters and physical characteristics of a plurality of nuclear power plant devices; creating a three-dimensional virtual model of the nuclear power plant device by using the design parameters and physical characteristics; combining the three-dimensional virtual model with real-time operation data of the nuclear power plant device to establish a digital twin (or can be understood as a real-time dynamic model of the nuclear power plant device) for reflecting the operation condition of the nuclear power plant device.

[0038] In one implementation, the historical operation records of the device can be extracted from the digital twin, and the extracted operation records can be analyzed to identify the typical operation mode of the device; the identified operation mode can be classified and arranged to form an operation state file of the device, and the historical operation data of the device can be summarized and analyzed by using the arranged operation state file, and then the historical operation data of the nuclear power plant device can be obtained. Specifically as follows:

[0039] Step 1: Collect the design drawings, specification parameters and physical characteristic data of the nuclear power plant device, including but not limited to material properties, size, weight distribution and other information.

[0040] Step 2: Analyze the acquired information and extract parameters critical for establishing the digital twin, such as the maximum load capacity of the equipment, operating temperature range, pressure limits, etc.

[0041] Step 3: Use the design parameters and physical property data obtained in Step 1 to create a three-dimensional virtual model of the equipment using computer-aided design (CAD) software.

[0042] Step 4: Refine the three-dimensional model by adding details that accurately represent the structural characteristics of the real equipment.

[0043] Step 5: Combine the three-dimensional virtual model created in Step 3 with real-time data collected during the equipment's operation using sensors and Internet of Things (IoT) technology.

[0044] Step 6: Establish a real-time dynamic model of the equipment by analyzing and processing the collected data, enabling simulation of the equipment's operating conditions under different scenarios.

[0045] Step 7: Continuously monitor the equipment's state changes using the real-time dynamic model established in Step 6, updating the model with real-time data to reflect the actual equipment's operating conditions.

[0046] Step 8: Analyze the monitored data to identify any trends or abnormal behavior indicating a decline in equipment performance.

[0047] Step 9: Extract historical operational records from the digital twin, including timestamps and related parameters for equipment start-up, shutdown, maintenance, and other activities.

[0048] Step 10: Analyze the operational records extracted in Step 9 to identify typical operating patterns of the equipment.

[0049] Step 11: Organize and categorize the operating patterns identified in Step 10 to create a running status profile for the equipment.

[0050] Step 12: Use the running status profile organized in Step 11 to analyze the equipment's historical operating data, providing insights into the overall operating trends of the equipment.

[0051] Through these steps, a digital twin that accurately reflects the real-time state of the nuclear power plant equipment is constructed, and historical operating data is collected, laying the foundation for further analysis of the equipment's health status.

[0052] Step 102: Determine the operating state characteristics of the nuclear power plant equipment based on the historical operating data.

[0053] Optionally, before analyzing the equipment operation state features by using the historical operation data, the historical operation data can also be pre-processed, including but not limited to data cleaning, correction or rejection of abnormal values, and filling of missing values by using appropriate statistical methods, to ensure the validity and integrity of the data.

[0054] In some embodiments of the present disclosure, the performance parameters of the equipment can be extracted from the historical operation data, including but not limited to temperature, pressure, vibration frequency, and other key indicators; the extracted performance parameters are analyzed to identify the change trend of the nuclear power plant equipment during operation, such as the change curve over time or periodic fluctuation; and the operation state is determined according to the change trend, for example, the normal working interval of the equipment, the performance degradation trend, etc.

[0055] In step 103, the target parameter reflecting the health condition of the nuclear power plant equipment is determined according to the operation state feature.

[0056] According to the operation state feature obtained in step 102, the target parameter reflecting the health condition of the nuclear power plant equipment can be selected, such as the temperature rise rate, the vibration amplitude increase, etc.

[0057] In step 104, the target parameter is compared with the preset threshold range of the target parameter, and the health evaluation index of the nuclear power plant equipment is determined based on the comparison result.

[0058] In one implementation, the threshold range of the target parameter can be preset to define the standard of the equipment health level, i.e., to determine the upper and lower limits of the health state. The target parameter is compared with the preset threshold range of the target parameter to evaluate the current health condition of the equipment. The health evaluation index of the equipment is quantified according to the comparison result, for example, the health degree of the equipment is represented by using percentage. Thus, not only the operation state feature of the equipment can be accurately analyzed, but also the health evaluation index of the equipment can be determined from the operation state feature, which provides strong support for further predicting the future health trend of the equipment.

[0059] In step 105, the probability of the nuclear power plant equipment failing in the future time period is predicted according to the health evaluation index.

[0060] In some embodiments of the present disclosure, the historical health state change of the equipment can be analyzed by using the health evaluation index to determine the health state change rule of the nuclear power plant equipment; the health trend of the nuclear power plant equipment in the future time period is predicted according to the change rule; a plurality of potential failure types of the nuclear power plant equipment and the risk level of each potential failure type are identified based on the health trend; the possibility of occurrence is evaluated by comprehensively considering the plurality of potential failure types and the risk level of each potential failure type, and the probability of the nuclear power plant equipment failing in the future time period is determined. Specifically as follows:

[0061] Step 1: Analyze the historical health status changes of the equipment using the determined health assessment indicators, including the trends of equipment performance parameters over time.

[0062] Step 2: Based on the analysis results of step 1), identify the change patterns of the equipment health status, such as linear decline or nonlinear change of performance parameters, etc.

[0063] Step 3: According to the change patterns identified in step 2), predict the health trend of the equipment in the future period of time.

[0064] Step 4: Record the results predicted in step 3) for subsequent steps to reference.

[0065] Step 5: Analyze the health trend predicted in step 3) to identify potential abnormal situations of the equipment.

[0066] Step 6: According to the abnormal situations identified in step 5), determine the potential fault types of the equipment, such as overheating, vibration intensification, etc.

[0067] Step 7: Risk level classification of the fault types determined in step 6), to assess the likelihood of their occurrence.

[0068] Step 8: Comprehensive risk level classification results in step 7), calculate the probability of equipment failure.

[0069] The probability of equipment failure is calculated, assuming that the probability of equipment failure of a certain type is affected by multiple factors, the following formula can be used to calculate the probability of equipment failure:

[0070]

[0071] Where P fault is the total probability of equipment failure. n is the number of factors affecting equipment failure. ω i is the weight coefficient corresponding to the i-th factor, indicating the influence degree of the factor on equipment failure. P i is the probability of equipment failure caused by the i-th factor. The weight coefficient ω i and the probability P i can be determined based on historical data, expert opinions or statistical methods. By considering all relevant factors, the accurate probability of equipment failure is obtained.

[0072] Step 106, based on the probability of failure, generate the replacement strategy of the nuclear power plant equipment.

[0073] In some embodiments of the present disclosure, high-risk failure points can be identified based on failure probabilities, and preventive measures can be designed for the identified high-risk failure points. In combination with the preventive measures, the maintenance cycle and content of the equipment can be formulated, and a preventive maintenance plan document can be formed as an execution guide.

[0074] In some embodiments of the present disclosure, the replacement strategy can also be updated based on the equipment maintenance plan. Referring to the formulated preventive maintenance plan, the maintenance frequency of the equipment can be determined, and the remaining service life of the equipment can be evaluated based on the maintenance frequency. In combination with the evaluation results, it can be judged whether the equipment needs to be replaced in advance, and the replacement strategy of the equipment can be updated according to the judgment results. Specifically as follows:

[0075] Step 1: Identify high-risk failure points based on failure probabilities, i.e. key components or systems that may cause equipment failure.

[0076] Step 2: Design preventive measures for high-risk failure points, including but not limited to regular inspection, lubrication maintenance, component replacement, etc.

[0077] Step 3: Formulate the maintenance cycle and content of the equipment in combination with the preventive measures, including the specific date of maintenance, the task list that needs to be performed, etc.

[0078] Step 4: Form a preventive maintenance plan document as an execution guide to ensure the standardization and normalization of maintenance work.

[0079] Step 5: Determine the maintenance frequency of the equipment, i.e. the interval time of the maintenance cycle, by referring to the preventive maintenance plan.

[0080] Step 6: Evaluate the remaining service life of the equipment based on the maintenance frequency, considering factors such as the aging degree and wear condition of the equipment.

[0081] Step 7: Judge whether the equipment needs to be replaced in advance in combination with the evaluation results, and consider replacing the equipment in advance if the remaining service life of the equipment is below a predetermined threshold.

[0082] Step 8: Update the replacement strategy of the equipment according to the judgment results, including the replacement time and the selection of replacement spare parts, etc.

[0083] Through the above steps, a preventive maintenance plan can be effectively formulated, and the replacement strategy of the equipment can be updated according to the maintenance plan, so as to improve the operation efficiency and safety of the equipment in the nuclear power plant.

[0084] Optionally, in some embodiments, the replacement strategy can also be sent to the terminal device held by the nuclear power plant execution personnel, scheduling the maintenance or replacement work of the device; recording the specific implementation details of the maintenance or replacement, obtaining the replacement strategy execution result of the nuclear power plant device; sending the replacement strategy execution result to the digital twin for data synchronization, updating its data model. With the updated data model, the running state of the device is continuously monitored, forming a closed-loop control. Specifically as follows:

[0085] Step 1: According to the updated replacement strategy, schedule the maintenance or replacement work of the device, including determining the specific maintenance or replacement task, the required resources, the execution personnel, etc.

[0086] Step 2: Perform the work scheduled in Step 1 and record the specific implementation details of the maintenance or replacement, such as the execution date, the execution personnel, the tools and spare parts used, etc.

[0087] Step 3: Feedback the implementation details recorded after executing the replacement strategy to the digital twin, update its data model, including updating the state parameters of the device, the historical maintenance record, etc.

[0088] Step 4: Continue to monitor the running state of the device with the updated digital twin, to ensure that the digital twin can reflect the latest running condition of the real device.

[0089] Step 5: Form a closed-loop control system by continuously updating the data model of the digital twin and keeping it synchronized with the running state of the actual device, to ensure that the maintenance strategy of the device is always up-to-date and can respond to changes in the state of the device in a timely manner.

[0090] Through the above steps, not only can the updated replacement strategy be executed, but also the execution result can be fed back to the digital twin, forming a closed-loop control, so as to ensure the efficient operation and safe maintenance of the nuclear power plant device.

[0091] By implementing the embodiments of the present disclosure, the historical running data of the nuclear power plant device is analyzed to obtain the running state characteristics and health evaluation indicators, and the probability of future failure is predicted to formulate a more scientific and reasonable preventive replacement strategy, which significantly improves the precision and efficiency of the nuclear power plant device maintenance, reduces the risk of unplanned downtime, and enhances the safety and economic benefits of the nuclear power plant.

[0092] Figure 2 A schematic diagram of a nuclear power plant device replacement strategy generation device provided by the embodiments of the present disclosure is shown in FIG. 1. Figure 2 As shown in FIG. 1, the nuclear power plant device replacement strategy generation device includes an acquisition module 201, a first determination module 202, a second determination module 203, a third determination module 204, a prediction module 205, and a strategy generation module 206.

[0093] The obtaining module 201 is configured to obtain the historical operation data of the nuclear power plant equipment by using a pre-constructed digital twin.

[0094] The first determining module 202 is configured to determine the operation state feature of the nuclear power plant equipment based on the historical operation data.

[0095] The second determining module 203 is configured to determine a target parameter reflecting the health condition of the nuclear power plant equipment according to the operation state feature.

[0096] The third determining module 204 is configured to compare the target parameter with a preset threshold range of the target parameter, and determine a health evaluation index of the nuclear power plant equipment based on a comparison result.

[0097] The prediction module 205 is configured to predict a probability of a failure of the nuclear power plant equipment in a future time period according to the health evaluation index.

[0098] The strategy generation module 206 is configured to generate a replacement strategy of the nuclear power plant equipment based on the probability of the failure.

[0099] In some embodiments of the present disclosure, the prediction module 205 is specifically configured to: determine a health state change rule of the nuclear power plant equipment by using the health evaluation index; predict a health trend of the nuclear power plant equipment in the future time period according to the change rule; identify a plurality of potential failure types of the nuclear power plant equipment and a risk level of each potential failure type based on the health trend; and determine the probability of the failure of the nuclear power plant equipment in the future time period by comprehensively considering the plurality of potential failure types and the risk level of each potential failure type.

[0100] In some embodiments of the present disclosure, on the basis of the embodiment as shown in Figure 2 The replacement strategy generation apparatus of the nuclear power plant equipment can further include a construction module. The construction module is configured to: obtain design parameters and physical characteristics of the nuclear power plant equipment; create a three-dimensional virtual model of the nuclear power plant equipment by using the design parameters and the physical characteristics; and combine the three-dimensional virtual model with real-time operation data of the nuclear power plant equipment to establish a digital twin reflecting the operation condition of the nuclear power plant equipment.

[0101] As to the apparatus in the above-mentioned embodiments, the specific manners in which the modules perform operations have been described in detail in the embodiments of the method, and will not be described here in detail.

[0102] In order to implement the above-mentioned embodiments, the present disclosure further proposes an electronic device, which includes a processor and a memory connected with the processor in communication; the memory stores computer execution instructions; and the processor executes the computer execution instructions stored in the memory to implement the method provided in the above-mentioned embodiments.

[0103] To achieve the above-mentioned embodiments, the present disclosure further provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to implement the method provided by the foregoing embodiments.

[0104] To achieve the above-mentioned embodiments, the present disclosure further provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the method provided by the foregoing embodiments.

[0105] In the foregoing embodiment description, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples without contradiction.

[0106] In addition, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly specified.

[0107] Any process or method descriptions in flow charts or otherwise described herein represent embodiments that can be understood as a module, segment, or portion of code that includes one or more executable instructions for implementing the specified logical function or process. The scope of the preferred embodiments of the present disclosure includes additional implementation in which the functions described in the illustrated or discussed order are performed in a different order, including substantially simultaneously, or in reverse order, according to the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0108] The logic and / or steps represented in flow diagrams or otherwise described herein, for example, can be considered as a sequence of instructions to implement logic functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device, such as a computer-based system, processor- containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In the context of this specification, a "computer-readable medium" can be any means that can contain, store, communicate, propagate or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be a machine-readable storage device (e.g., magnetic, optical or other) a machine-readable storage diskette (e.g., floppy disk, optical disk, CD- ROM, etc.), a machine- readable storage card (e.g., PCMCIA card, etc.), a machine-readable storage tape (e.g., magnetic tape, optical tape, etc.), a machine-readable storage medium (e.g., RAM, ROM, etc.), a machine-readable signal (e.g., electrical, optical, etc.), a machine-readable medium (e.g., carrier wave, etc.) or any other suitable medium or means of embodying the program. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a RAM, a ROM, an EPROM, a FLASH memory card, an optical fiber, and a portable compact disc read-only memory (CD-ROM). Additionally, the computer-readable medium can be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and stored in a computer memory.

[0109] It should be understood that portions of the present disclosure can be implemented in hardware, software, firmware or combinations thereof. In the above embodiments, the various steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As such, if implemented in hardware, and in another embodiment, any of the following technologies, known in the art, or their combinations can be used: discrete logic circuitry having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and the like.

[0110] Those skilled in the art can understand that all or part of the steps carried out by the above-mentioned embodiment methods can be completed by programs instructing related hardware, and the programs can be stored in a computer-readable storage medium. When the programs are executed, one or a combination of the steps of the method embodiments is included.

[0111] In addition, each functional unit in each embodiment of the present disclosure can be integrated in one processing module, or each unit can exist physically separately, or two or more units can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software functional module. When the integrated module is realized in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0112] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A method for generating a replacement strategy for nuclear power plant equipment, characterized in that: The following steps are involved: Use pre-built digital twins to obtain historical operating data of nuclear power plant equipment; determining operating status characteristics of the nuclear power plant equipment based on the historical operating data; determining, based on the operating status characteristics, target parameters for reflecting the health status of the nuclear power plant equipment; comparing the target parameter with a preset threshold range of the target parameter, and determining a health assessment index of the nuclear power plant equipment based on the comparison result; Predicting the probability of failure of the nuclear power plant equipment in a future time period based on the health assessment indicators; A replacement strategy for the nuclear power plant equipment is generated based on the probability of failure.

2. The method according to claim 1, characterized in that The identifying the operating status characteristics of the nuclear power plant equipment based on the historical operating data includes: identifying, by means of the historical operating data, a change trend of the nuclear power plant equipment during operation; The operating status is determined according to the change trend.

3. The method according to claim 1, characterized in that The predicting, based on the health assessment indicator, the probability of failure of the nuclear power plant equipment in a future time period includes: Determining a health status change pattern of the nuclear power plant equipment using the health assessment index; predicting the health trend of the nuclear power plant equipment in a future time period based on the change law; identifying a plurality of potential failure types of the nuclear power plant equipment and a risk level of each of the potential failure types based on the health trend; The probability of failure of the nuclear power plant equipment in a future time period is determined by comprehensively considering multiple potential failure types and the risk level of each potential failure type.

4. The method according to claim 1, wherein The digital twin is pre-built through the following steps: Obtaining design parameters and physical characteristics of the nuclear power plant equipment; creating a three-dimensional virtual model of the nuclear power plant equipment using the design parameters and the physical properties; The three-dimensional virtual model is combined with the real-time operating data of the nuclear power plant equipment to establish the digital twin that reflects the operating status of the nuclear power plant equipment.

5. The method according to any one of claims 1 to 4, characterized in that Also includes: sending the replacement strategy to a terminal device held by an executive of the nuclear power plant; Obtaining a replacement strategy execution result for the nuclear power plant equipment; The replacement strategy execution result is sent to the digital twin for data synchronization.

6. A device for generating a replacement strategy for nuclear power plant equipment, characterized in that: include: An acquisition module, used to acquire historical operating data of nuclear power plant equipment using pre-built digital twins; A first determining module, configured to determine operating status characteristics of the nuclear power plant equipment based on the historical operating data; A second determining module is configured to determine a target parameter reflecting the health status of the nuclear power plant equipment according to the operating status characteristics; a third determining module, configured to compare the target parameter with a preset threshold range of the target parameter, and determine a health assessment index of the nuclear power plant equipment based on the comparison result; A prediction module, configured to predict the probability of failure of the nuclear power plant equipment in a future time period based on the health assessment indicator; A strategy generating module is used to generate a replacement strategy for the nuclear power plant equipment based on the probability of the failure.

7. The device according to claim 6, characterized in that The prediction module is specifically used for: Determining a health status change pattern of the nuclear power plant equipment using the health assessment index; predicting the health trend of the nuclear power plant equipment in a future time period based on the change law; identifying a plurality of potential failure types of the nuclear power plant equipment and a risk level of each of the potential failure types based on the health trend; The probability of failure of the nuclear power plant equipment in a future time period is determined by comprehensively considering multiple potential failure types and the risk level of each potential failure type.

8. The device according to claim 6, characterized in that The device further comprises a building block; wherein the building block is configured to: Obtaining design parameters and physical characteristics of the nuclear power plant equipment; creating a three-dimensional virtual model of the nuclear power plant equipment using the design parameters and the physical properties; The three-dimensional virtual model is combined with the real-time operating data of the nuclear power plant equipment to establish the digital twin that reflects the operating status of the nuclear power plant equipment.

9. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 5 when executed by a processor.

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