A full-link design method of an intelligent operation monitoring system for a nuclear power plant

Abstract

This application discloses a full-link design method for an intelligent operation monitoring system in a nuclear power plant, comprising: acquiring monitoring characteristic parameters and design input parameters; the monitoring characteristic parameters including one or more of the monitoring frequency, monitored objects, anomaly identification methods, and intervention methods under manual monitoring conditions; and the design input parameters including the design objectives and constraints of the intelligent operation monitoring system; determining the application constraint parameters, overall configuration parameters, and functional configuration parameters of the intelligent operation monitoring system based on the monitoring characteristic parameters and design input parameters; obtaining the intelligent operation monitoring system based on the overall configuration parameters; calibrating and verifying the intelligent operation monitoring system; and iteratively optimizing the intelligent operation monitoring system based on the verification results. This application achieves standardized design and stable deployment of an intelligent operation monitoring system for nuclear power plants by constructing a full-link design method covering design input analysis, system configuration determination, core element development, and calibration iteration.

Description

Technical Field

[0001] This application relates to the field of nuclear power safety technology, and in particular to a full-link design method for an intelligent operation monitoring system for nuclear power plants. Background Technology

[0002] Nuclear power, as a green, stable, and clean energy source, is characterized by safety and economy, which are also the cornerstones of its survival and development. A healthy unit condition is a prerequisite for ensuring the safety, stability, and economic efficiency of nuclear power. This is achieved by monitoring the variable status of nuclear power equipment; that is, the real-time measurement values ​​of these variables characterize whether the unit is currently in a healthy state. Real-time monitoring of these variables is not only a requirement of the first level of nuclear safety defense-in-depth, but also a key daily task for operators in the control room.

[0003] In accordance with the technical requirements and management regulations for the safe and economical operation of nuclear power plants, and based on the established scope and frequency, control room operators periodically monitor the real-time measured values ​​of various variables by browsing the screens on the digital instrumentation and control system set up on the control panel. This is done to identify early anomalies in the equipment and intervene in a timely manner to prevent further deterioration and equipment failure, which would ultimately affect the safety and economy of the unit. This work is commonly referred to as panel monitoring. Generally, control room operators monitor variables at a certain frequency (intervals vary from every 2 hours to every 4 hours) and identify and judge possible anomalies based on their knowledge and operational experience. The main disadvantages of this approach include: discontinuous monitoring; large workload and high intensity; high skill requirements; difficulty in identifying early anomalies; and complex intervention and handling methods. To achieve 24 / 7 and intelligent control room monitoring in nuclear power plants, transforming the traditional work from "people finding problems" to "problems finding people," reducing the workload of control room operators and the risk of human error, thereby improving the safety, reliability, and economy of nuclear power units, it is necessary to develop an intelligent operation monitoring system for nuclear power plants.

[0004] Existing technology CN115204638A discloses a method for implementing an intelligent monitoring system in a power plant. It uses standard protocols such as OPC and DA to collect, isolate, and store historical data from multiple control system tag numbers. The aim is to define the range of data to be monitored in the monitoring system and provide a foundation for subsequent historical data analysis. It defines indicators to establish the correspondence between collected data tag numbers and indicators, and adds L3 / L2 / L1 / H1 / H2 / H3 limits to address the need for repeated referencing of the same tag number and the definition of limits within the system. However, this solution fails to achieve 24 / 7 and intelligent monitoring in the nuclear power plant's main control room and fails to reduce the workload of the main control room operators and the risk of human error.

[0005] Existing technology CN119472357A discloses an unmanned intelligent monitoring system and method for power plants, including a power plant pipeline data acquisition unit. Taking the unmanned intelligent monitoring system for power plant pipelines as an example, the power plant pipeline data acquisition unit is used to collect real-time relevant data of pipelines within the power plant, process the collected real-time relevant data for subsequent use, and store and record the processed real-time relevant data of pipelines within the power plant. This solution fails to achieve 24 / 7 and intelligent monitoring of the main control room of a nuclear power plant, and fails to reduce the workload of the main control room operators and the risk of human error.

[0006] In summary, neither of the two existing technologies mentioned above has achieved 24 / 7 and intelligent monitoring of the main control room in a nuclear power plant, nor has it reduced the workload of the main control room operators or the risk of human error. Summary of the Invention

[0007] The purpose of this application is to solve the aforementioned technical problems.

[0008] To achieve the above objectives, the first aspect of this application proposes a full-link design method for an intelligent operation monitoring system for nuclear power plants, including: Acquire monitoring characteristic parameters and design input parameters. Monitoring characteristic parameters include one or more of the monitoring intensity, monitoring object, anomaly identification method and intervention method under manual monitoring conditions. Design input parameters include the design objectives and constraints of the intelligent operation monitoring system. Based on the monitoring characteristic parameters and design input parameters, determine the application constraint parameters, overall configuration parameters, and functional configuration parameters of the intelligent operation monitoring system; An intelligent operation monitoring system is derived based on overall configuration parameters; The intelligent operation monitoring system was calibrated and verified, and iterative optimization was carried out based on the verification results.

[0009] Furthermore, the intelligent operation monitoring system based on the overall configuration parameters includes: object grouping steps based on the overall configuration parameters, algorithm selection steps, threshold setting steps, early warning strategy configuration steps, model building steps, model training and optimization steps, and model encapsulation steps, thus forming the intelligent operation monitoring system.

[0010] Furthermore, the application constraint parameters include unit operating conditions and service objects, the overall configuration parameters include performance indicators and technical routes, and the functional configuration parameters include functional division, functional implementation, and functional management.

[0011] Furthermore, the technical approach includes at least a multi-algorithm collaboration mechanism, a multi-threshold fusion mechanism, and a multi-level early warning linkage mechanism.

[0012] Furthermore, performance metrics should include at least the false negative rate, false positive rate, and computation response time.

[0013] Furthermore, the object grouping step includes grouping systems according to the functions of the nuclear power system, and classifying and grouping the variable parameters within each system according to their importance; the algorithm selection step includes formulating an algorithm selection method, and combining and matching algorithms based on the results of the object grouping step.

[0014] Furthermore, the threshold setting step includes determining the threshold type, configuring the fusion logic of various thresholds, and setting the range of thresholds and bandwidth; the early warning strategy configuration step includes dividing the early warning level, configuring the early warning logic and the corresponding intervention process.

[0015] Furthermore, the model building steps include model structure selection, model construction, and model deployment; the model training and optimization steps include training based on test data from the simulation simulator, training based on real operating data of the unit, and adjusting and optimizing model parameters according to the training results; the model packaging steps include model parameter configuration, model packaging, and interface protocol configuration.

[0016] Furthermore, the calibration and verification of the intelligent operation monitoring system includes reliability acceptance, performance index acceptance, functional configuration acceptance, and compliance acceptance.

[0017] Furthermore, the monitoring characteristic parameters and design input parameters are obtained, including by analyzing the management regulations, behavioral norms, on-site operation processes and simulated operation processes related to the manual operation monitoring of nuclear power plants to obtain the monitoring characteristic parameters.

[0018] Furthermore, the acquisition of monitoring characteristic parameters and design input parameters also includes obtaining design input parameters by analyzing the functional and performance requirements proposed by the user and the technical implementation scheme proposed by the designer.

[0019] By applying the above-described technical solution of the present invention, at least the following technical effects are achieved: 1. This invention can significantly improve the development efficiency and operational quality of intelligent operation monitoring systems for nuclear power plants. Through a systematic and phased design process, it ensures the comprehensiveness and systematic nature of the design, effectively avoiding repetitive work and resource waste in the design process. At the same time, through continuous iteration in the design optimization phase, it can quickly respond to and improve problems found in actual operation, ensuring that the intelligent operation monitoring system can adapt to the complex environment of nuclear power plant operation and improve the stability, reliability and intelligence of the system. 2. This invention, through in-depth analysis of the current status of manual operation monitoring in nuclear power plants, clearly defines the requirements for intelligent operation monitoring, providing a clear direction for subsequent stages, avoiding the problem of design being out of touch with actual needs, and ensuring that the intelligent operation monitoring system can accurately meet the intelligent upgrade requirements of nuclear power plants; 3. The technical approach of this invention ensures the continuity and feasibility of the system design and development process, avoids technical blind spots and design fragmentation, and improves design efficiency; the core element R&D stage enhances the functionality and data processing capabilities of the intelligent operation monitoring system through specific technical implementation. 4. This invention ensures the quality and safety of the intelligent operation monitoring system before it is put into actual operation through comprehensive acceptance testing of the system's reliability, performance indicators, functional requirements, and compliance, thus avoiding potential technical risks and operational errors.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0021] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 A flowchart of a full-link design method for an intelligent operation monitoring system for a nuclear power plant, according to one embodiment, is presented; Figure 2 A detailed flowchart of the end-to-end design method for an intelligent operation monitoring system for nuclear power plants, according to another embodiment, is presented. Detailed Implementation

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] The present invention will be further described in detail below with reference to specific embodiments, which should not be construed as limiting the scope of protection claimed by the present invention.

[0024] According to one aspect of the present invention, a full-link design method for an intelligent operation monitoring system for nuclear power plants is proposed.

[0025] like Figure 1 The present invention illustrates a full-link design method for an intelligent operation monitoring system for nuclear power plants according to an embodiment of the present invention. The process mainly includes the following steps: S1. Obtain monitoring characteristic parameters and design input parameters. Monitoring characteristic parameters include one or more of the following under manual monitoring conditions: monitoring intensity, monitoring object, anomaly identification method, and intervention method. Design input parameters include the design objectives and constraints of the intelligent operation monitoring system.

[0026] This step is the design initiation phase. The main tasks are to conduct an analysis of the current status of manual operation monitoring in nuclear power plants to obtain monitoring characteristic parameters and to conduct a study on the requirements of intelligent operation monitoring to obtain design input parameters. The two are in a cause-and-effect relationship.

[0027] Furthermore, by analyzing the management regulations, behavioral norms, on-site operation processes, and simulated operation processes related to manual operation monitoring in nuclear power plants, monitoring characteristic parameters were obtained.

[0028] By analyzing the current status of manual operation monitoring in nuclear power plants, including analysis of management regulations and code of conduct, on-site observation, interviews with relevant parties, simulator demonstrations, and sand table simulations, the monitoring characteristic parameters of manual operation monitoring were obtained.

[0029] To comprehensively and thoroughly understand the pain points and shortcomings of manual operation monitoring, a multi-pronged approach is needed, involving analysis of management regulations and codes of conduct, on-site observation, interviews with stakeholders, simulator demonstrations, and scenario-based exercises. The analysis of the operating unit's management regulations and codes of conduct for operation monitoring serves as the theoretical foundation; while on-site observation and interviews with stakeholders further refine and supplement the theoretical analysis through practical experience. However, this combination of theory and practice also has limitations, such as the knowledge and understanding limitations of those who drafted the management regulations and codes of conduct, and the insufficient experience of stakeholders with operation monitoring tasks. Using simulator exercises and scenario-based exercises can largely address these shortcomings. By simulating possible operating states of the unit, various scenarios of manual operation monitoring can be reproduced, and the operations and behaviors of manual operation monitoring can be simulated in each scenario, thereby maximizing the identification of the pain points and shortcomings of manual operation monitoring.

[0030] Specifically, in this embodiment, the analysis of the current status of manual operation monitoring includes: analyzing and studying the requirements of nuclear power unit management and operation units such as "Operation Duty Management", "Operator Behavior Code", and "Operation Inspection Management"; observing operators performing manual operation monitoring tasks in the main control room of some nuclear power bases; conducting surveys and interviews on manual operation monitoring tasks for operators in some nuclear power main control room, and conducting drills using simulators.

[0031] The pain points and challenges of manual monitoring include: the discontinuity of manual monitoring, the large workload and high intensity, the high requirements for the professional skills of the implementers, the difficulty in identifying anomalies, and the complexity of intervention and handling methods.

[0032] Furthermore, by analyzing the functional and performance requirements proposed by the user and the technical implementation schemes proposed by the design team, design input parameters are obtained.

[0033] The research on the requirements for intelligent operation monitoring includes studying the implementation requirements of intelligent operation monitoring at the user end and studying the design schemes for intelligent operation monitoring at the design end.

[0034] Specifically, in this embodiment, the research on intelligent operation monitoring requirements includes: from the user's perspective, intelligent operation monitoring implementation requirements are proposed from the angles of completing monitoring tasks more efficiently and accurately, improving the high-tech content of nuclear power, simplifying workflows, and reducing workload; from the design perspective, intelligent operation monitoring design schemes are proposed by combining the overall design principles and concepts of smart nuclear power plants, the development trends and technological maturity of cutting-edge artificial intelligence technologies, the safety and economic goals of nuclear power plants, and good practices in intelligent design in other power industries.

[0035] Step S1 is the cornerstone of initiating the full-chain design work for the intelligent operation monitoring system of a nuclear power plant, playing a decisive role in whether subsequent steps can be carried out meticulously, effectively, and fully. This technical solution revolves around the core element of "uncovering the pain points and key needs of manual operation monitoring": building upon the analysis of the current state of manual operation monitoring, it provides input for the research on the requirements of intelligent operation monitoring. Through forward and reverse analysis, they complement and reinforce each other to form a complete requirement chain, avoiding omissions.

[0036] S2. Based on the monitoring characteristic parameters and design input parameters, determine the application constraint parameters, overall configuration parameters and functional configuration parameters of the intelligent operation monitoring system.

[0037] Furthermore, the application constraint parameters include unit operating conditions and service objects, the overall configuration parameters include performance indicators and technical routes, and the functional configuration parameters include functional division, functional implementation, and functional management.

[0038] The application scenarios of the intelligent operation monitoring system for nuclear power plants are determined by applying constraint parameters, including the applicable unit operating conditions, service targets, and product positioning. The overall scheme of the intelligent operation monitoring system for nuclear power plants is determined by overall configuration parameters, including the overall development concept, performance indicators, and technical route. The functional requirements of the intelligent operation monitoring system for nuclear power plants are determined by functional configuration parameters, including the functional division, implementation, and management of the intelligent operation monitoring system for nuclear power plants.

[0039] This step first analyzes the application scenarios of the intelligent operation monitoring system to define the product positioning; based on the product positioning, it clarifies the overall plan, including the technical route and performance indicators; then, through functional division, implementation, and management, it matches the characteristics of the technical route and the performance indicator requirements.

[0040] Specifically, in this embodiment, the nuclear power plant intelligent operation monitoring system is applicable to the steady-state operation of the unit. As an auxiliary support system, it mainly serves personnel involved in the management, operation, maintenance, supervision, and training of nuclear power plants. In addition, it also provides key points and breakthroughs for unit improvement for nuclear power plant designers and technical transformation personnel.

[0041] Specifically, in this embodiment, the functions of the nuclear power plant intelligent operation monitoring system include real-time online monitoring and deterioration early warning, auxiliary operation and maintenance decision-making, and automation of short-cycle periodic tests.

[0042] Furthermore, the technical approach includes at least a multi-algorithm collaboration mechanism, a multi-threshold fusion mechanism, and a multi-level early warning linkage mechanism.

[0043] Furthermore, performance metrics should include at least the false negative rate, false positive rate, and computation response time.

[0044] Specifically, in this embodiment, the intelligent operation monitoring system for nuclear power plants adopts a technical approach of multi-algorithm collaboration mechanism, multi-threshold fusion mechanism, and multi-level early warning linkage mechanism; performance indicators include: false alarm rate, false alarm rate, calculation response time, coverage of monitoring objects, measurement point range, system reliability, system stability, and benefit contribution.

[0045] S3. An intelligent operation monitoring system is obtained based on the overall configuration parameters.

[0046] Furthermore, based on the overall configuration parameters, the system performs steps such as object grouping, algorithm selection, threshold setting, early warning strategy configuration, model building, model training and optimization, and model encapsulation to form an intelligent operation monitoring system.

[0047] Furthermore, the object grouping step includes grouping systems according to the functions of the nuclear power system, and classifying and grouping the variable parameters within each system according to their importance; the algorithm selection step includes formulating an algorithm selection method, and combining and matching algorithms based on the results of the object grouping step.

[0048] Furthermore, the threshold setting step includes determining the threshold type, configuring the fusion logic of various thresholds, and setting the range of thresholds and bandwidth; the early warning strategy configuration step includes dividing the early warning level, configuring the early warning logic and the corresponding intervention process.

[0049] Furthermore, the model building steps include model structure selection, model construction, and model deployment; the model training and optimization steps include training based on test data from the simulation simulator, training based on real operating data of the unit, and adjusting and optimizing model parameters according to the training results; the model packaging steps include model parameter configuration, model packaging, and interface protocol configuration.

[0050] In this embodiment, the intelligent algorithm consists of one or more algorithms combined, including one or more of AAKR, MSET, SPRT, LSTM, KPCA, SVM, Clustering, PCA, and AANN. The structure and basic principles of each algorithm are well known to those skilled in the art. Given the scarcity of fault data and the numerous and complex types of faults in the nuclear power field, this embodiment uses normal unit operation data for modeling, reconstructs the optimal estimate using intelligent algorithms, and then identifies anomalies by comparing the measured values ​​with the optimal estimate (residual calculation and evaluation). The model training process includes the following steps: First, multivariate operating parameter data are collected from the historical operating conditions of the nuclear power plant, and the data is preprocessed, including outlier removal, missing data completion, and normalization. Second, the preprocessed historical operating data is divided into training and validation datasets, which are then input into the aforementioned prediction models for training and validation, respectively. The training parameters for each model are pre-set according to the model type or determined through cross-validation, including the number of hidden layer nodes, learning rate, and number of training epochs in neural network models, and window length and threshold parameters in statistical models. After model training, the model prediction error is evaluated based on the validation data. When the prediction accuracy meets the preset requirements, the model is established. During model operation, the real-time measured variable parameter data from the nuclear power plant is input into the trained prediction model to calculate the optimal estimate for the corresponding variable parameter. The optimal estimate is compared with the actual measured value to obtain the residual. The operating status of each variable parameter is determined based on the magnitude and trend of the residual.

[0051] In this step, we adopt a multi-algorithm collaboration mechanism, a multi-threshold fusion mechanism, and a multi-level early warning linkage mechanism as our technical approach. With the false negative rate, false positive rate, and computation response time as key performance indicators, we carry out research and development on the following steps: object grouping, algorithm selection, threshold setting, early warning strategy configuration, model building, model training and optimization, and model packaging, to form an intelligent operation monitoring system.

[0052] The final intelligent operation monitoring system realizes the development and implementation of hardware and software. The hardware includes hardware configuration and hardware performance, while the software includes software functions, human-machine interface, and human factors engineering.

[0053] During the product development and implementation process, the requirements for both hardware and software are considered: the hardware configuration must meet the requirements of accuracy, timeliness and safety in the control and information transmission of nuclear power generation; the software must meet the user's requirements for convenience, user-friendliness and practicality, and both hardware and software should conform to the human factors engineering specifications for nuclear power units.

[0054] S4. Calibrate and verify the intelligent operation monitoring system, and iteratively optimize the intelligent operation monitoring system based on the verification results.

[0055] Furthermore, the intelligent operation monitoring system undergoes reliability acceptance, performance indicator acceptance, functional configuration acceptance, and compliance acceptance.

[0056] Calibration and verification is an inspection of the entire design process and output results. The reliability and performance indicators of the intelligent operation monitoring system are verified according to the overall configuration parameters in step S2; the functionality is verified to meet design requirements according to the functional configuration parameters in step S2; in addition, compliance verification is conducted in accordance with nuclear safety regulations, nuclear safety guidelines, national standards, and industry standards related to nuclear power unit operation and intelligent design.

[0057] Iterative optimization involves the partial or overall re-optimization and improvement of design results and product performance. At the design end, product upgrades and iterations are conducted based on the development trends of advanced intelligent technologies, the improvement plan for the digitalization level of nuclear power, and research on intelligent R&D and applications in other power industries. At the user end, product upgrades and iterations are conducted based on user feedback on the current intelligent operation monitoring system, performance and functional improvement needs, and the scope of system and parameter coverage.

[0058] like Figure 2 The diagram shows a detailed flowchart of the end-to-end design method for an intelligent operation monitoring system for a nuclear power plant, according to another embodiment.

[0059] By applying the above-described technical solution of the present invention, at least the following technical effects are achieved: 1. This invention can significantly improve the development efficiency and operational quality of intelligent operation monitoring systems for nuclear power plants. Through a systematic and phased design process, it ensures the comprehensiveness and systematic nature of the design, effectively avoiding repetitive work and resource waste in the design process. At the same time, through continuous iteration in the design optimization phase, it can quickly respond to and improve problems found in actual operation, ensuring that the intelligent operation monitoring system can adapt to the complex environment of nuclear power plant operation and improve the stability, reliability and intelligence of the system. 2. This invention, through in-depth analysis of the current status of manual operation monitoring in nuclear power plants, clearly defines the requirements for intelligent operation monitoring, providing a clear direction for subsequent stages, avoiding the problem of design being out of touch with actual needs, and ensuring that the intelligent operation monitoring system can accurately meet the intelligent upgrade requirements of nuclear power plants; 3. The technical approach of this invention ensures the continuity and feasibility of the system design and development process, avoids technical blind spots and design fragmentation, and improves design efficiency; the core element R&D stage enhances the functionality and data processing capabilities of the intelligent operation monitoring system through specific technical implementation. 4. This invention ensures the quality and safety of the intelligent operation monitoring system before it is put into actual operation by comprehensively accepting the system's reliability, performance indicators, functional requirements, and compliance, thus avoiding potential technical risks and operational errors.

[0060] The above are merely several specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

[0061] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0062] It should be noted that, in the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

Claims

1. A full-link design method for an intelligent operation monitoring system for nuclear power plants, characterized in that, include: Acquire monitoring characteristic parameters and design input parameters. The monitoring characteristic parameters include one or more of the monitoring intensity, monitoring object, anomaly identification method and intervention method under manual monitoring conditions. The design input parameters include the design objectives and constraints of the intelligent operation monitoring system. Based on the monitoring characteristic parameters and the design input parameters, the application constraint parameters, overall configuration parameters, and functional configuration parameters of the intelligent operation monitoring system are determined. The intelligent operation monitoring system is obtained based on the overall configuration parameters; The intelligent operation monitoring system was calibrated and verified, and iterative optimization was carried out based on the verification results.

2. The end-to-end design method according to claim 1, characterized in that, The intelligent operation monitoring system based on the overall configuration parameters includes: Based on the overall configuration parameters, the system performs the following steps: object grouping, algorithm selection, threshold setting, early warning strategy configuration, model building, model training and optimization, and model encapsulation, thus forming an intelligent operation monitoring system.

3. The end-to-end design method according to claim 1, characterized in that, The application constraint parameters include unit operating conditions and service objects; the overall configuration parameters include performance indicators and technical routes; and the functional configuration parameters include functional division, functional implementation, and functional management.

4. The end-to-end design method according to claim 3, characterized in that, The technical approach includes at least a multi-algorithm collaboration mechanism, a multi-threshold fusion mechanism, and a multi-level early warning linkage mechanism.

5. The end-to-end design method according to claim 3, characterized in that, The performance metrics include at least the false negative rate, false positive rate, and computation response time.

6. The end-to-end design method according to claim 2, characterized in that, The object grouping step includes grouping systems according to the functions of the nuclear power system, and classifying and grouping the variable parameters within each system according to their importance; the algorithm selection step includes formulating an algorithm selection method, and combining and matching algorithms based on the results of the object grouping step.

7. The end-to-end design method according to claim 2, characterized in that, The threshold setting step includes determining the threshold type, configuring the fusion logic of various thresholds, and setting the range of thresholds and bandwidth; the early warning strategy configuration step includes dividing the early warning level, configuring the early warning logic and the corresponding intervention process.

8. The end-to-end design method according to claim 2, characterized in that, The model building steps include model structure selection, model construction, and model deployment; the model training and optimization steps include training based on test data from the simulation simulator, training based on actual operating data of the unit, and adjusting and optimizing model parameters according to the training results; the model encapsulation steps include model parameter configuration, model encapsulation, and interface protocol configuration.

9. The end-to-end design method according to claim 1, characterized in that, The calibration and verification of the intelligent operation monitoring system includes, The intelligent operation monitoring system was subjected to reliability acceptance, performance index acceptance, functional configuration acceptance, and compliance acceptance.

10. The end-to-end design method according to claim 1, characterized in that, The acquisition of monitoring feature parameters and design input parameters includes, By analyzing the management regulations, behavioral norms, on-site operation processes, and simulated operation processes related to manual operation monitoring in nuclear power plants, monitoring characteristic parameters were obtained.

11. The end-to-end design method according to claim 10, characterized in that, The acquisition of monitoring feature parameters and design input parameters also includes, By analyzing the functional and performance requirements proposed by the users and the technical implementation solutions proposed by the designers, the design input parameters are obtained.

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