Abnormity processing method and system based on nuclear power plant technical specification, and related medium

Abstract

The embodiment of the invention provides an exception handling method and system based on a nuclear power plant technical specification, and a related medium, and belongs to the technical field of nuclear power plant operation management. The method comprises the steps of obtaining real-time operation data of a nuclear power plant; wherein system identification information for identifying a data source is configured in the real-time operation data; determining a target operation mode of the nuclear power plant based on the real-time operation data; matching an applicable target rule group from a plurality of preset event rule groups according to the system identification information and the target operation mode; wherein the event rule group is constructed through the content of a technical specification; and based on the target rule group, performing anomaly identification on the real-time operation data, and according to a triggered target event rule, obtaining target processing information corresponding to the target event rule. According to the embodiment of the invention, efficient utilization of the technical specification can be realized.

Description

Technical Field

[0001] The present application relates to the technical field of nuclear power plant operation management, and in particular to an abnormality handling method, system and related media based on a nuclear power plant technical specification. Background Art

[0002] The technical specification is an important operating document for nuclear power plants, but the text volume is very large. Its content records hundreds of events and corresponding thousands of measures. It is an important reference document for the operation of nuclear power plants. The technical specification records a large number of operating restrictions (Limiting Conditions For Operation, LCO) for the normal operation of nuclear power plants. Operating restrictions are a set of technical parameters that must be met by equipment or systems in different operating modes of nuclear power plants. These operating restrictions are set to ensure the safe operation of nuclear power plants. They define the acceptable operating range of nuclear power plant systems under specific conditions.

[0003] However, in the prior art, the use of technical specifications is not efficient. In some cases, in work practice, the use of technical specifications only relies on the memory of the crew operators and the method of paper document query, which is inefficient. Even if the technical specifications can now be digitized, the crew operators are required to consult them multiple times. And because a device or system in a nuclear power plant is often related to multiple operating restrictions, and the conditions of the nuclear power plant during actual operation are complex, multiple events are often triggered at the same time. For the crew operators, it is difficult to sort out the situation and adopt specific countermeasures at this time. Therefore, how to efficiently use the contents of the technical specifications to cope with the complex operating conditions of nuclear power plants has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose an exception handling method, system and related media based on the technical specifications of a nuclear power plant, aiming to achieve efficient use of the technical specifications.

[0005] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes an abnormality handling method based on a nuclear power plant technical specification, the method comprising:

[0006] Acquiring real-time operation data of a nuclear power plant; wherein the real-time operation data is configured with system identification information identifying a data source;

[0007] determining a target operation mode of the nuclear power plant based on the real-time operation data;

[0008] According to the system identification information and the target operation mode, matching an applicable target rule group from a plurality of preset event rule groups; wherein the event rule group is constructed according to the content of the technical specification;

[0009] Based on the target rule group, the real-time operation data is identified as abnormal, and according to the triggered target event rule, the target processing information corresponding to the target event rule is obtained.

[0010] In some embodiments, before matching an applicable target rule group from a plurality of preset event rule groups according to the system identification information and the target operation mode, the method further includes constructing the event rule group based on a technical specification, specifically including:

[0011] Perform character recognition processing on the contents recorded in the technical specification to obtain text data of the specification;

[0012] Analyze the applicable scope according to the specification text data to obtain multiple rule applicable condition information;

[0013] Perform rule event analysis according to the specification text data to obtain event rule data;

[0014] The event rule data is grouped based on each rule application condition information to obtain the corresponding event rule group.

[0015] In some embodiments, performing rule event parsing according to the specification text data to obtain event rule data includes:

[0016] Based on the text data of the specification, the text content is parsed to obtain the operation restriction conditions, the measure plan information, the event processing time and the abnormality inspection frequency; wherein the event processing time indicates the time reserved for solving the abnormal problem, and the abnormality inspection frequency indicates the frequency of actively inspecting the equipment or function;

[0017] generating an abnormality determination condition according to the operation restriction condition;

[0018] Generate an exception handling plan corresponding to the operation restriction condition according to the measure plan information;

[0019] Constructing an abnormal event rule based on the abnormality determination condition, the abnormality handling solution, the event handling time, and the abnormality inspection frequency;

[0020] All the abnormal event rules are integrated to obtain event rule data.

[0021] In some embodiments, each of the triggered target event rules is converted into an abnormal trigger event and stored in an event record database to obtain historical event data. Based on the target rule group, the real-time operation data is identified as abnormal, and according to the triggered target event rule, the target processing information corresponding to the target event rule is obtained, including:

[0022] Based on the target rule group, determining a correlation range in the historical event data to obtain a potential correlation event group;

[0023] Performing abnormality identification according to the real-time operation data, obtaining the triggered target event rule, and generating a corresponding target trigger event;

[0024] Performing correlation matching in the potential correlation event group based on the target trigger event to obtain multiple target correlation events;

[0025] Based on the target triggering event and the plurality of target associated events, corresponding target processing information is obtained.

[0026] In some embodiments, association matching is performed in the potential association event group based on the target trigger event to obtain multiple target association events, including:

[0027] Determine the event triggering factor and event triggering time corresponding to the target triggering event through the target event rule corresponding to the target triggering event;

[0028] A plurality of associated target associated events are determined from the potential associated event group based on the event triggering factor and the event triggering time.

[0029] In some embodiments, before performing association matching in the potential association event group based on the target trigger event to obtain multiple target association events, the process further includes constructing an event association network, which specifically includes:

[0030] Obtaining the event triggering time and event triggering factor corresponding to each of the abnormal triggering events;

[0031] Based on the event triggering time and the event triggering factors, a knowledge graph is constructed for each corresponding abnormal triggering event to obtain an event association network.

[0032] In some embodiments, after obtaining corresponding target processing information based on the target triggering event and the plurality of target association events, the method further includes:

[0033] According to the triggered target event rule, generating the target trigger event configured with an event priority tag, an event trigger time and an event processing time;

[0034] Performing a criticality rating based on the event priority tag, the event triggering time, and the event processing time to obtain an event criticality rating of the target triggering event;

[0035] Based on the event criticality rating and the plurality of target-related events, criticality rating is performed to obtain a comprehensive criticality rating;

[0036] Event warning information is issued based on the comprehensive criticality rating.

[0037] In some embodiments, after performing abnormal identification on the real-time operation data based on the target rule group and obtaining target processing information corresponding to the target event rule according to the triggered target event rule, the target processing information is evaluated, specifically including:

[0038] Based on the target processing information, an abnormality repair process is performed on the target triggering event that triggers the target event rule to obtain an abnormality repair result;

[0039] Perform anomaly repair evaluation based on the anomaly repair result to obtain rule feedback information;

[0040] The target event rule is iterated based on the rule feedback information to obtain a target modification rule.

[0041] In some embodiments, the iterating the target event rule based on the rule feedback information to obtain the target modification rule includes:

[0042] Perform a simulation environment test according to the target modification rule to obtain rule test information;

[0043] Add the target modification rule to the target rule group according to the rule test information.

[0044] In some embodiments, the target operation mode of the nuclear power plant is determined based on the real-time operation data, and when the nuclear power plant needs to switch the operation mode, the method further includes:

[0045] Receiving an operation mode switching request and obtaining an operation mode to be switched;

[0046] Based on the operation mode to be switched, matching an applicable preliminary rule group from a plurality of preset event rule groups;

[0047] Performing an abnormal correlation evaluation based on the preliminary rule group and the triggered target event rule to obtain a mode switching suggestion;

[0048] The operation mode switching request is executed according to the mode switching suggestion.

[0049] In some embodiments, performing an abnormal correlation evaluation based on the preliminary rule group and the triggered target event rule to obtain a mode switching suggestion includes:

[0050] When the abnormal event rule included in the preliminary rule group is associated with the triggered target event rule, generating the mode switching suggestion that does not recommend switching the operating mode;

[0051] When the abnormal event rule included in the preliminary rule group is not associated with the triggered target event rule, the mode switching suggestion for recommending switching the operation mode is generated.

[0052] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application proposes an abnormality processing system based on a nuclear power plant technical specification, the system comprising a data acquisition module, a rule application scope determination module, an operation mode recognition module, and an abnormality recognition and processing module;

[0053] The data acquisition module is used to obtain real-time operation data of the nuclear power plant; wherein the real-time operation data is configured with system identification information identifying the source of the data;

[0054] The operation mode identification module is used to determine the target operation mode of the nuclear power plant based on the real-time operation data;

[0055] The rule application scope determination module is used to match an applicable target rule group from a plurality of preset event rule groups according to the system identification information and the target operation mode; wherein the event rule group is constructed according to the content of the technical specification;

[0056] The exception identification and processing module is used to identify exceptions on the real-time operation data based on the target rule group, and obtain target processing information corresponding to the target event rule according to the triggered target event rule.

[0057] In some embodiments, the system further comprises a rules database and an event record database;

[0058] The rule database is used to store the abnormal event rules in the event rule group;

[0059] The event record database is used to store abnormal trigger events converted according to the triggered target event rules, and record the event priority label, event triggering time and event processing time corresponding to the target event rules.

[0060] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the exception handling method based on the nuclear power plant technical specification described in the first aspect when executing the computer program.

[0061] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the exception handling method based on the nuclear power plant technical specification described in the first aspect above.

[0062] The abnormality handling method, system and related medium based on the technical specification of a nuclear power plant proposed in the present application obtain the real-time operation data of the nuclear power plant and identify the system identification information of the source of the real-time operation data. The current target operation mode of the nuclear power plant is determined by the real-time operation data, and then the applicable target rule group is matched from multiple event rule groups constructed by the content of the technical specification through the system identification information and the target operation mode. The real-time operation data is identified for abnormality through the target rule group. When an abnormality is found, the corresponding target event rule is triggered, and the corresponding target processing information can be obtained according to the target event rule. It can be seen that the present application constructs multiple event rule groups through the content of the technical specification, and determines the applicable target rule group based on the system identification information and the current target operation mode of the nuclear power plant, and then identifies the abnormality of the actual operation data of the nuclear power plant. When the target event rule is triggered, the corresponding target processing information is given. Thereby, the efficient use of the technical specification is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 is a flow chart of an abnormality handling method based on a nuclear power plant technical specification provided in an embodiment of the present application;

[0064] Figure 2 yes Figure 1 The flowchart before step S103 in FIG.

[0065] Figure 3 yes Figure 2 Flow chart of step S203 in FIG.

[0066] Figure 4 yes Figure 1 Flow chart of step S104 in FIG.

[0067] Figure 5 yes Figure 4 Flow chart of step S403 in FIG.

[0068] Figure 6 yes Figure 4 The flowchart before step S403 in FIG.

[0069] Figure 7 yes Figure 4 The flowchart after step S404 in FIG.

[0070] Figure 8 yes Figure 1 The flowchart after step S104 in FIG.

[0071] Fig. 9 yes Figure 8 Flow chart of step S803 in FIG.

[0072] Fig.10 is another flow chart of an abnormality handling method based on a nuclear power plant technical specification provided in an embodiment of the present application;

[0073] Fig.11 yes Fig.10 Flow chart of step S1003 in FIG.

[0074] Fig.12 It is a structural schematic diagram of an abnormality handling system based on a nuclear power plant technical specification provided in an embodiment of the present application;

[0075] Fig.13 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0076] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0077] It should be noted that, although the functional modules are divided in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0078] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0079] The embodiments of the present application provide an exception handling method, system and related media based on the technical specification of a nuclear power plant, aiming to achieve efficient use of the technical specification.

[0080] The exception handling method, system and related media based on the technical specifications of a nuclear power plant provided in the embodiments of the present application are specifically described through the following embodiments. First, the exception handling method based on the technical specifications of a nuclear power plant in the embodiments of the present application is described.

[0081] The exception handling method based on the technical specification of a nuclear power plant provided in the embodiment of the present application relates to the technical field of operation and management of nuclear power plants. The exception handling method based on the technical specification of a nuclear power plant provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server side, and can also be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or can be configured as a server cluster or a distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the exception handling method based on the technical specification of a nuclear power plant, etc., but is not limited to the above forms.

[0082] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0083] Figure 1 is an optional flow chart of an abnormality handling method based on a nuclear power plant technical specification provided in an embodiment of the present application, Figure 1 The method may include but is not limited to steps S101 to S104.

[0084] Step S101, acquiring real-time operation data of a nuclear power plant; wherein the real-time operation data is configured with system identification information identifying the source of the data;

[0085] Step S102, determining a target operation mode of the nuclear power plant based on real-time operation data;

[0086] Step S103, matching an applicable target rule group from a plurality of preset event rule groups according to the system identification information and the target operation mode; wherein the event rule group is constructed according to the content of the technical specification;

[0087] Step S104, based on the target rule group, anomaly identification is performed on the real-time operation data, and according to the triggered target event rule, target processing information corresponding to the target event rule is obtained.

[0088] Steps S101 to S104 shown in the embodiment of the present application are obtained by acquiring the real-time operation data of the nuclear power plant and by identifying the system identification information of the source of the real-time operation data. The current target operation mode of the nuclear power plant is determined by the real-time operation data, and then the applicable target rule group is matched from the multiple event rule groups constructed by the content of the technical specification through the system identification information and the target operation mode. The real-time operation data is identified as abnormal by the target rule group, and when an abnormality is found, the corresponding target event rule is triggered, and the corresponding target processing information can be obtained according to the target event rule. It can be seen that the present application constructs multiple event rule groups through the content of the technical specification, and determines the applicable target rule group based on the system identification information and the current target operation mode of the nuclear power plant, and then identifies the abnormality of the actual operation data of the nuclear power plant. When the target event rule is triggered, the corresponding target processing information is given. Thereby, the efficient use of the technical specification is achieved.

[0089] In step S101 of some embodiments, real-time operation data of a nuclear power plant is obtained. Real-time operation data generally includes various parameters and indicators, such as temperature, pressure, flow, vibration, etc., which are key information for evaluating the current state of a nuclear power plant. In order to ensure the accuracy and reliability of the data, the real-time operation data will contain system identification information, which is used to identify the source of the data.

[0090] The configuration of system identification information allows data to be traced back to a specific system or device, which is conducive to subsequent treatment measures. For example, if a sensor detects an abnormal reading, the system identification information can help operators quickly locate the specific sensor location and determine whether the reading is accurate or whether there is an equipment failure. In addition, system identification information can also help to distinguish between multiple similar systems or devices, especially in large nuclear power plants, where multiple sensors or systems of the same type may be operating simultaneously.

[0091] Through this step, the operation status of the nuclear power plant can be monitored in real time, providing necessary data support for the subsequent matching of abnormal event rules and abnormal identification. The acquisition of such real-time data is the key to realizing automated and intelligent operation management of nuclear power plants. It enables the contents of the technical specifications to be dynamically applied to actual operation, thus improving the operation efficiency and safety of nuclear power plants.

[0092] In step S102 of some embodiments, during the operation of a nuclear power plant, there are multiple different operation modes, each of which has its own specific operation parameters and requirements. These modes may include various states such as startup, power operation, maintenance, and shutdown, and each state has different effects on the equipment and systems of the nuclear power plant.

[0093] In order to ensure the safe and efficient operation of nuclear power plants, it is necessary to monitor in real time and accurately determine the current operation mode of the nuclear power plant. Real-time operation data contains the current status information of various systems and equipment in the nuclear power plant, such as key parameters such as temperature, pressure, flow, etc. Through in-depth analysis of these data, the current status of the nuclear power plant can be identified and matched with the preset operation mode, thereby determining the current target operation mode of the nuclear power plant.

[0094] In step S103 of some embodiments, the system analyzes the system identification information in the real-time operation data and the target operation mode of the nuclear power plant, and then matches the target rule group that best suits the real-time operation data from multiple event rule groups based on the system identification information and the target operation mode. Through techniques such as exact matching or pattern matching, the system can quickly find and apply the adapted target rule group. The event rule group is pre-constructed based on the content of the technical specification, and the event rule group contains several abnormal event rules, which represent the rules and conditions that should be followed when the nuclear power plant is operating.

[0095] The technical specification records in detail the operating constraints that a nuclear power plant should meet in various operating modes, including equipment performance parameters, safety thresholds, and operating procedures. By converting these operating constraints into abnormal event rules, a framework for analyzing and evaluating real-time data can be provided.

[0096] The implementation of this matching mechanism makes the monitoring system of nuclear power plants more flexible and efficient. It allows the system to dynamically select the most appropriate abnormal event rules for analysis based on the characteristics of real-time data, thereby improving the accuracy and response speed of monitoring. At the same time, this also reduces the workload of operators because they can rely on the system to automatically match and apply abnormal event rules instead of manually looking up and applying complex information in technical specifications.

[0097] In step S104 of some embodiments, after the target rule group is determined, the real-time operating data of the nuclear power plant is subjected to abnormal identification. In the complex operating environment of the nuclear power plant, the real-time monitoring system must be able to accurately identify any deviation from the normal operating parameters so as to take timely measures to ensure the safe and stable operation of the power plant.

[0098] The target rule group contains various operating restrictions and countermeasures specified in the technical specifications, which are the basis for evaluating whether the real-time operating data meets the safety standards. By comparing the real-time operating data with the abnormal event rules in the target rule group, the system can identify any abnormal situations, such as a parameter exceeding the set safety threshold or the equipment operating status not meeting the expected pattern.

[0099] Once an anomaly is identified, the system will provide countermeasures corresponding to the operating restrictions in the technical specification, i.e., target processing information, based on the triggered target event rules. This automated response mechanism not only improves the efficiency of handling abnormal situations, but also reduces the possibility of human error.

[0100] In some embodiments, the present application uses the technology of rule engine to build an event rule group. A rule engine is a software component that is designed to handle complex business logic and decision making. The main purpose of the rule engine is to separate event rules from application code for easy management and maintenance. The operating parameters and safety regulations of nuclear power plants may need to be updated according to the latest technical and regulatory requirements, and the flexibility of the rule engine makes these updates easier to implement. A large number of operating restrictions and corresponding measures are recorded in the technical specifications of nuclear power plants. The use of rule engines can add, delete or modify abnormal event rules very flexibly, and the rule engine is designed with the growth of the number of rules in mind, so it can easily handle hundreds or thousands of rules. Advanced rule engines usually include performance optimization mechanisms, such as caching, indexing and reasoning mechanisms, which are crucial for processing a large number of rules. Therefore, the rule engine can handle a large number of abnormal event rules obtained through technical specifications conversion very well. On the other hand, there are complex operating modes and functional interactions between systems and equipment in nuclear power plants, and the rule engine supports functions such as conflict detection, rule reasoning and simulation execution, which can solve this problem well and can handle application scenarios containing a large number of conditional judgments and complex logic. In some embodiments, the rule engine and logic diagram can also be used in combination, with the rule engine being responsible for processing complex business logic, especially those exception event rules that require frequent updates and maintenance, and the logic diagram being used to visualize the rule flow in the rule engine to help users better understand the behavior of the rule engine. A logic diagram can be used to represent the decision-making process within the rule engine. For example, a decision tree-shaped logic diagram can be created to show what measures should be taken under different conditions. In this way, the rule engine can ensure the accuracy and efficiency of the logic processing, while the logic diagram provides an intuitive view to help non-technical personnel better understand the working principle of the rule engine, thereby enhancing the transparency and usability of the system.

[0101] See also Figure 2In some embodiments, before step S103, the process further includes constructing an event rule group based on the technical specification, which may include but is not limited to steps S201 to S204:

[0102] Step S201, performing character recognition processing on the content recorded in the technical specification to obtain specification text data;

[0103] Step S202, performing application scope analysis according to the specification text data to obtain multiple rule application condition information;

[0104] Step S203, performing rule event analysis according to the specification text data to obtain event rule data;

[0105] Step S204: grouping the event rule data based on each rule applicable condition information to obtain a corresponding event rule group.

[0106] In step S201 of some embodiments, character recognition processing is performed on the original content of the technical specification, which generally refers to converting the specification in paper documents or PDF format into editable and analyzable text data. This can be achieved through optical character recognition technology or other language model technologies.

[0107] In step S202 of some embodiments, multiple rule application condition information is extracted by parsing the obtained specification text data. In the technical specification, the rule application condition information defines the specific conditions under which the operating restrictions or countermeasures are applicable, such as a specific operating mode, device status or environmental parameters. Through this step, it can be clear which rules should be triggered under what circumstances.

[0108] In step S203 of some embodiments, the specification text data is further analyzed to identify and construct specific abnormal event rules. Abnormal event rules are restriction rules converted by operating restriction conditions, and they define the actions that the nuclear power plant must take when certain situations are detected. This step converts the text description in the specification into structured abnormal event rule data, providing clear guidance for subsequent real-time monitoring.

[0109] In step S204 of some embodiments, based on the previously extracted rule applicability condition information, the abnormal event rules in the event rule data are grouped to form multiple event rule groups. Each event rule group contains a series of abnormal event rules that should be considered and applied under specific conditions. Such grouping processing enables the system to quickly match and apply the correct abnormal event rules during real-time monitoring, thereby improving the efficiency of abnormal identification and response.

[0110] Through steps S201 to S204, the complex text information in the technical specification can be converted into abnormal event rules that can be used for real-time monitoring, providing strong support for the safe operation of the nuclear power plant. This method not only improves the accuracy of the application of abnormal event rules, but also greatly improves the automation and intelligence level of the management of nuclear power plants based on technical specifications.

[0111] See also Figure 3 In some embodiments, step S203 may include but is not limited to steps S301 to S305:

[0112] Step S301, parsing the text content based on the specification document text data to obtain operation restriction conditions, measure plan information, event processing time and abnormality inspection frequency; wherein the event processing time indicates the time reserved for solving abnormal problems, and the abnormality inspection frequency indicates the frequency of actively inspecting the equipment or function;

[0113] Step S302, generating an abnormality determination condition according to the operation restriction condition;

[0114] Step S303, generating an exception handling plan corresponding to the operation restriction condition according to the measure plan information;

[0115] Step S304, constructing abnormal event rules based on abnormality determination conditions, abnormality handling solutions, event processing time and abnormality inspection frequency;

[0116] Step S305: Integrate all abnormal event rules to obtain event rule data.

[0117] In step S301 of some embodiments, by parsing the text content of the specification, important operating parameters are extracted, including operating restrictions, measures and solutions information, event processing time and abnormal inspection frequency. Operating restrictions are technical parameters that must be followed for the safe operation of nuclear power plants, and measures and solutions information indicates the countermeasures to be taken in specific abnormal situations. Event processing time is the time window allowed for solving abnormal problems, and abnormal inspection frequency determines the period for active inspection of equipment or systems.

[0118] In step S302 of some embodiments, abnormality determination conditions for real-time monitoring are generated based on the extracted operation constraints, which define under what parameters or states the system should consider an abnormality and trigger an alarm.

[0119] In step S303 of some embodiments, a corresponding abnormality handling scheme is generated for each operation restriction condition according to the previously obtained measure scheme information. That is, an abnormality handling scheme corresponding to each abnormality determination condition is generated. These schemes include specific operation steps that should be performed when an abnormality is detected to ensure that the nuclear power plant can respond in time and take correct measures.

[0120] In step S304 of some embodiments, an abnormal event rule is constructed by combining the abnormality determination conditions, abnormality handling scheme, event handling time and abnormality inspection frequency. This step integrates the previously separated information into a complete abnormal event rule, each of which includes not only the conditions for determining the abnormality, but also a detailed plan for how to respond once the abnormality occurs.

[0121] In step S305 of some embodiments, all constructed abnormal event rules are integrated to form event rule data. These event rule data will be further grouped and processed according to the rule applicable condition information. This provides a comprehensive rule base for the real-time monitoring system, allowing the system to quickly and accurately identify abnormalities and take predefined measures in different target operation modes and situations.

[0122] In some embodiments, the operator can also customize the abnormal judgment conditions, abnormal handling schemes, event handling time and abnormal inspection frequency through the input area for creating abnormal event rules configured by the system. This means that the operator can set specific parameters or thresholds based on the abnormal event rules given in the technical specifications and according to the specific needs and operating experience of the nuclear power plant, and flexibly adjust and optimize the monitoring and handling process of abnormal events, thereby improving the overall operating efficiency and safety performance. It is also possible to create new abnormal event rules that are more suitable for detecting and judging abnormalities based on some highly correlated abnormal events in the technical specifications.

[0123] In some embodiments, the operator can also test whether the triggering and operation of abnormal event rules are normal through the control area configured by the system for testing abnormal event rules, such as whether the status cause of the abnormal triggering event is described correctly and whether the event processing time is reasonable.

[0124] In some embodiments, the operator also has the authority to eliminate or reset an abnormal triggering event that has occurred, so as to eliminate or reset an abnormal triggering event of an erroneous triggering or test.

[0125] In some embodiments, since abnormal event rules are grouped based on system identification information, relevant staff can query the abnormal event rules that are in effect based on the information of the device, or manage the abnormal event rules.

[0126] See also Figure 4In some embodiments, each triggered target event rule is converted into an abnormal trigger event and stored in an event record database to obtain historical event data. Step S104 may include but is not limited to steps S401 to S404:

[0127] Step S401, based on the target rule group, determine the association range in the historical event data to obtain a potential association event group;

[0128] Step S402, performing abnormality identification according to the real-time operation data, obtaining the triggered target event rule, and generating the corresponding target trigger event;

[0129] Step S403, performing association matching in the potential associated event group based on the target trigger event to obtain multiple target associated events;

[0130] Step S404: obtaining corresponding target processing information based on the target triggering event and multiple target associated events.

[0131] In step S401 of some embodiments, firstly, based on the target rule group, the potential correlation range is determined in the historical event data to identify other events that may be related to the current anomaly. This step analyzes the historical data to find events that are similar to or causally related to the current anomaly condition, thereby obtaining a group of potential related events. This helps the system understand the full picture of the anomaly, rather than just looking at a single event in isolation.

[0132] In step S402 of some embodiments, real-time operation data is used to identify anomalies. During this process, the system obtains the triggered target event rule according to the abnormal event rule in the target rule group. When the target event rule is triggered, the system generates a corresponding target trigger event, which records the specific circumstances and triggering conditions of the abnormality in detail. The target trigger event is essentially the same as the abnormal trigger event, except that the abnormal trigger event is historical data stored in the event record database.

[0133] In step S403 of some embodiments, the system will perform in-depth correlation matching in the previously determined potential correlation event group based on the target trigger event. This step is to discover other events related to the current anomaly, whether these events are direct causes or indirect effects. In this way, the system can identify multiple target correlation events, providing more information for comprehensive understanding and handling of anomalies.

[0134] In step S404 of some embodiments, the system will comprehensively consider the target triggering event and the identified multiple target associated events to determine the best processing solution. This step involves in-depth analysis of the event and evaluation of possible processing measures to obtain corresponding target processing information. This information will guide the operator to take appropriate actions to resolve the anomaly and restore the normal operation of the system.

[0135] Through step S401 to step S404, a comprehensive and in-depth abnormality handling process is formed. This process can not only respond to abnormalities in real time, but also provide a more comprehensive perspective and more effective handling solutions by analyzing historical data and identifying related events. This not only improves the safety and reliability of nuclear power plant operation, but also optimizes the efficiency and effectiveness of event handling.

[0136] See also Figure 5 In some embodiments, step S403 may include but is not limited to steps S501 to S502:

[0137] Step S501, determining the event triggering factor and event triggering time corresponding to the target triggering event through the target event rule corresponding to the target triggering event;

[0138] Step S502: determining a plurality of associated target associated events from the potential associated event group based on the event triggering factor and the event triggering time.

[0139] In step S501 of some embodiments, the event triggering factor and triggering time of the triggering event are determined according to the target event rule corresponding to the target triggering event. The event triggering factor refers to the specific condition or parameter that causes the rule to be triggered, such as a sensor reading exceeding a preset safety threshold. The event triggering time is the specific moment when the target event rule is triggered, which is very important for understanding the timing and dynamic changes of the target triggering event.

[0140] In step S502 of some embodiments, based on the event triggering factor and the event triggering time, target associated events that are deeply related to the current target triggering event are screened out from the potential associated event group. This screening process may involve comparison of timestamps, matching of event types, and analysis of abnormal sources. In this way, the system can identify those target associated events that are closely related to the current target triggering event in time and logic.

[0141] The significance of this step is that it not only helps operators quickly locate the root cause of the anomaly, but also predicts possible chain reactions and secondary effects. For example, if a device failure triggers a series of protection actions, these protection actions may also be considered as events associated with the initial failure event. By identifying these associated events, operators can more comprehensively assess the impact of the anomaly and take appropriate measures to avoid potential risks.

[0142] See also Figure 6 In some embodiments, the steps before step S403 may include but are not limited to steps S601 to S602:

[0143] Step S601, obtaining the event triggering time and event triggering factor corresponding to each abnormal triggering event;

[0144] Step S602: Based on the event triggering time and the event triggering factors, a knowledge graph is constructed for each corresponding abnormal triggering event to obtain an event association network.

[0145] In steps S601 to S602 of some embodiments, the system constructs an event association network based on historical event data, and associates each abnormal trigger event with associated factors in chronological order. The event trigger factor and event trigger time of each abnormal trigger event can be associated by constructing a knowledge graph to construct an event association network. This can better help operators trace abnormal trigger events that occurred in the past, and can also help determine associated target associated events from a potential associated event group.

[0146] In some embodiments, the associated target associated event is determined from the potential associated event group based on the system identification information configured by the real-time operating data that triggers the target trigger event, or the functional module involved in the target trigger event, so as to more comprehensively evaluate the abnormal source and development process of the abnormal trigger event.

[0147] Through step S501 to step S502, an effective event correlation analysis process is formed. This process provides strong support for the abnormality handling of nuclear power plants by deeply analyzing the triggering factors and time of the abnormality and accurately matching the potential related events. This not only improves the accuracy and efficiency of abnormality handling, but also enhances the safety and reliability of the entire system.

[0148] See also Figure 7 In some embodiments, step S404 may include but is not limited to steps S701 to S704:

[0149] Step S701, generating a target trigger event configured with an event priority tag, event trigger time and event processing time according to the triggered target event rule;

[0150] Step S702, performing a criticality rating based on the event priority tag, event triggering time, and event processing time to obtain an event criticality rating of the target triggering event;

[0151] Step S703, performing a criticality rating based on the event criticality rating and multiple target-related events to obtain a comprehensive criticality rating;

[0152] Step S704: issuing event warning information according to the comprehensive criticality rating.

[0153] In step S701 of some embodiments, a target trigger event configured with an event priority tag, an event trigger time, and an event processing time is generated according to the triggered target event rule. The event priority tag is a key parameter that classifies events according to their severity and urgency. The event trigger time records the specific moment when the rule is triggered, and the event processing time is the time window allowed to resolve the abnormal problem.

[0154] In step S702 of some embodiments, a criticality rating is performed based on the event priority tag, event triggering time, and event processing time to determine the urgency and possible impact of the event, and obtain the event criticality rating of the target triggering event. For example, in some embodiments, due to insufficient event processing, adverse effects may occur, and its criticality rating will be high, which means that immediate action is required to respond.

[0155] In step S703 of some embodiments, this rating process is further extended to multiple target-related events to obtain a comprehensive criticality rating. In this step, the system will comprehensively consider all related events, including their mutual influence and potential chain reactions, to obtain a comprehensive criticality rating. This rating not only considers the criticality of individual events, but also their potential impact on the safety of nuclear power plant operation as a whole.

[0156] In step S704 of some embodiments, the system will issue an event warning information based on the comprehensive criticality rating. This warning information will provide details of the event, including its criticality, possible impact, and recommended response measures. The warning information can be issued through a variety of channels, including the control room alarm system, email, text message, or automatic voice call, etc., to ensure that all relevant personnel can receive notifications in a timely manner and take necessary actions.

[0157] Through steps S701 to S704, the safety monitoring system of the nuclear power plant can respond to abnormal events quickly and accurately, and ensure that all relevant personnel can understand the situation and response measures of the event in a timely manner. This not only improves the safety and reliability of the nuclear power plant, but also improves the efficiency and effectiveness of responding to emergencies.

[0158] See also Figure 8 In some embodiments, step S104 further includes evaluating the target processing information, which may include but is not limited to steps S801 to S803:

[0159] Step S801, performing an abnormality repair process on the target triggering event that triggers the target event rule based on the target processing information to obtain an abnormality repair result;

[0160] Step S802, performing anomaly repair evaluation based on the anomaly repair result to obtain rule feedback information;

[0161] Step S803, iterating the target event rule based on the rule feedback information to obtain the target modification rule.

[0162] In step S801 of some embodiments, an abnormality repair process is performed on the target triggering event that triggers the target event rule based on the target processing information. In this step, the operator or the automatic system will execute the countermeasures given by the target processing information to solve or alleviate the abnormal event. These countermeasures may include adjusting device parameters, restarting the system, executing specific maintenance procedures, etc. After executing the countermeasures, the system will record the abnormality repair results, including whether the processing is successful or not, the effect of the processing, and any observed side effects.

[0163] In step S802 of some embodiments, the system will perform an anomaly repair evaluation based on the anomaly repair result. This evaluation process involves analyzing the effect of the anomaly repair process to determine whether the problem has been successfully solved and whether the expected goal has been achieved. The evaluation result will generate rule feedback information, which is crucial for understanding the effectiveness and efficiency of the current target event rules.

[0164] In step S803 of some embodiments, the system will iterate the target event rule based on the rule feedback information. This iteration process may include adjusting the abnormality determination conditions, modifying the processing plan, updating the event processing time, or adjusting the abnormality inspection frequency. In this way, the nuclear power plant can continuously learn and improve, making the event rules more accurate and effective.

[0165] Through steps S801 to S803, a continuous improvement cycle based on experience feedback is implemented together. By evaluating the abnormal repair results and updating the event rules accordingly, the nuclear power plant can improve its ability to respond to abnormal triggering events, reduce the probability of similar events in the future, and improve the overall operational safety and reliability. This self-optimization and learning ability is a key feature of modern nuclear power plant management, helping to ensure that nuclear power plants maintain the highest safety standards under changing operating conditions.

[0166] See also Fig. 9 In some embodiments, step S803 may include but is not limited to steps S901 to S902:

[0167] Step S901, performing a simulation environment test according to the target modification rule to obtain rule test information;

[0168] Step S902: Add the target modification rule to the target rule group according to the rule test information.

[0169] In step S901 of some embodiments, before the target modification rule is applied to actual operation, it needs to be fully tested and verified. The target modification rule is first tested in a simulation environment. The simulation environment is a low-risk testing platform that can simulate the actual operating conditions of a nuclear power plant, allowing operators or engineers to evaluate the modification effects of the target modification rules without interfering with the real system. In the simulation test, various hypothetical situations can be created, including equipment failures, parameter anomalies, etc., to verify whether the target modification rules can be correctly triggered and guide appropriate processing measures. In this way, the accuracy, reliability and efficiency of the target modification rules can be verified to ensure that the target modification rules can effectively identify and respond to abnormal events in actual applications.

[0170] In step S902 of some embodiments, after completing the simulation environment test, the target modification rule is added to the target rule group according to the rule test information. This step is to integrate the verified rules into the formal monitoring system of the nuclear power plant. After the target modification rules are added to the target rule group, they will begin to play a role in the actual monitoring process, guiding the operator or the automatic system to respond to abnormal events.

[0171] Through step S901 to step S902, the nuclear power plant can ensure that all target modification rules have been strictly tested and verified, thereby ensuring the continuity and safety of nuclear power plant operation. This rigorous testing and review process helps reduce potential risks caused by errors in target modification rules, enhances the nuclear power plant's ability to respond to abnormal events, and improves overall operating efficiency and safety.

[0172] See also Fig.10In some embodiments, when the nuclear power plant needs to switch the operation mode, the method may also include but is not limited to steps S1001 to S1004:

[0173] Step S1001, receiving an operation mode switching request, and obtaining an operation mode to be switched;

[0174] Step S1002, matching an applicable preliminary rule group from a plurality of preset event rule groups based on the operation mode to be switched;

[0175] Step S1003, performing an abnormal correlation evaluation based on the preliminary rule group and the triggered target event rule to obtain a mode switching suggestion;

[0176] Step S1004: executing an operation mode switching request according to the mode switching suggestion.

[0177] In step S1001 of some embodiments, when the nuclear power plant needs to switch the operation mode, the control system of the nuclear power plant will receive an operation mode switching request. This request may come from an operator or may be determined by an automatic system. The request specifies the operation mode to be switched, and the operation mode to be switched refers to the operation mode to which the request is switched.

[0178] In step S1002 of some embodiments, the system will match an applicable preparatory rule group from a plurality of preset event rule groups based on the operation mode to be switched. The preparatory rule group includes abnormal event rules and parameters corresponding to the operation mode to be switched, and these abnormal event rules define how the system should respond to different abnormal events in the new operation mode.

[0179] In step S1003 of some embodiments, the system will perform an abnormal correlation evaluation based on the preliminary rule group and the triggered target event rules. This step is to query the triggered target event rules to see if there are some abnormal triggering events that will affect the switched operation mode, predict the abnormal situations that may occur after switching the operation mode, and generate a mode switching suggestion, suggesting whether to respond to the operation mode switching request and switch the operation mode.

[0180] In step S1004 of some embodiments, the control system will execute the operation mode switching request according to the mode switching suggestion. This step includes updating system parameters, adjusting device settings, notifying relevant personnel, etc. to ensure the smoothness and safety of the switching process.

[0181] See also Fig.11 In some embodiments, step S1003 may include but is not limited to steps S1101 to S1102:

[0182] Step S1101, when the abnormal event rule included in the preliminary rule group is associated with the triggered target event rule, a mode switching suggestion is generated that does not recommend switching the operating mode;

[0183] Step S1102 : when the abnormal event rule included in the preliminary rule group is not associated with the triggered target event rule, a mode switching suggestion for recommending switching the operation mode is generated.

[0184] In step S1101 of some embodiments, if the abnormal event rule included in the preliminary rule group is associated with the target event rule that has been triggered, the system will generate a mode switching suggestion that does not recommend switching the operating mode. This association may mean that the current abnormal event has not been properly handled, and switching to the operating mode to be switched may aggravate the existing problem. For example, if an abnormal event related to the cooling system is occurring, and the new operating mode requires higher cooling efficiency, then switching may increase the pressure on the cooling system. In this case, it is recommended not to switch until the current abnormal event is resolved.

[0185] In step S1102 of some embodiments, if the abnormal event rule in the preliminary rule group is not associated with the triggered target event rule, this indicates that switching to the new operation mode is unlikely to be affected by the current abnormal event. In this case, the system generates a mode switching suggestion for recommending switching the operation mode. This may be because the current abnormal event has been isolated or resolved, or the new operation mode has enough buffer to handle potential problems.

[0186] Through step S1101 to step S1102, the nuclear power plant can carefully analyze the correlation between the preliminary rule group and the triggered target event rule based on the existing triggered target event rule to determine whether to switch the operation mode. This helps to ensure the smoothness and safety of the nuclear power plant operation mode switching and prevent possible risks and problems.

[0187] The embodiment of the present application obtains the real-time operation data of the nuclear power plant and identifies the system identification information of the source of the real-time operation data. The current target operation mode of the nuclear power plant is determined through the real-time operation data, and then the applicable target rule group is matched from multiple event rule groups constructed through the content of the technical specification through the system identification information and the target operation mode. The real-time operation data is identified as abnormal through the target rule group. When an abnormality is found, the corresponding target event rule is triggered, and the corresponding target processing information can be obtained according to the target event rule. It can be seen that the present application constructs multiple event rule groups through the content of the technical specification, and determines the applicable target rule group based on the system identification information and the current target operation mode of the nuclear power plant, and then identifies the abnormality of the actual operation data of the nuclear power plant. When the target event rule is triggered, the corresponding target processing information is given. Thereby, the efficient use of the technical specification is achieved.

[0188] See also Fig.12 The embodiment of the present application also provides an exception handling system based on the technical specification of a nuclear power plant, which can implement the above-mentioned exception handling method based on the technical specification of a nuclear power plant. The system includes a data acquisition module, a rule application scope determination module, an operation mode recognition module, and an exception recognition and processing module:

[0189] The data acquisition module is used to obtain the real-time operation data of the nuclear power plant; wherein the real-time operation data is configured with system identification information identifying the source of the data;

[0190] The operation mode identification module is used to determine the target operation mode of the nuclear power plant based on real-time operation data;

[0191] The rule application scope determination module is used to match an applicable target rule group from a plurality of preset event rule groups according to the system identification information and the target operation mode; wherein the event rule group is constructed according to the content of the technical specification;

[0192] The exception identification and processing module is used to identify exceptions in real-time operation data based on the target rule group, and obtain target processing information corresponding to the target event rule according to the triggered target event rule.

[0193] The specific implementation of the abnormality handling system based on the technical specification of a nuclear power plant is substantially the same as the specific implementation of the abnormality handling method based on the technical specification of a nuclear power plant described above, and will not be described in detail herein.

[0194] See also Fig.12In some embodiments, the system further includes a rule database and an event record database. The rule database is used to store the abnormal event rules in the event rule group. The event record database is used to store the abnormal triggering events converted according to the triggered target event rules, and record the event priority label, event triggering time and event processing time of the corresponding target event rules.

[0195] The operator can export the abnormal trigger events stored in the event record database, or sort or query them according to certain standards and display them through the historical query module configured by the system. The abnormal trigger event is the event generated based on the trigger target event rule.

[0196] In some embodiments, the operator can display the target triggering events that have occurred and the corresponding target processing information in a terminal, so as to facilitate the relevant staff to respond and check the situation in time.

[0197] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned exception handling method based on the technical specification of the nuclear power plant when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0198] See also Fig.13 , Fig.13 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0199] The processor 1301 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.

[0200] The memory 1302 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1302 can store an operating system and other applications. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1302, and the processor 1301 calls and executes the exception handling method based on the nuclear power plant technical specification of the embodiment of this application;

[0201] Input / output interface 1303, used to implement information input and output;

[0202] The communication interface 1304 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WI FI, Bluetooth, etc.);

[0203] A bus 1305 that transmits information between the various components of the device (e.g., the processor 1301, the memory 1302, the input / output interface 1303, and the communication interface 1304);

[0204] The processor 1301 , the memory 1302 , the input / output interface 1303 and the communication interface 1304 are connected to each other in communication within the device via a bus 1305 .

[0205] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned exception handling method based on the technical specification of the nuclear power plant is implemented.

[0206] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0207] The exception handling method, system and related medium based on the technical specification of a nuclear power plant provided in the embodiment of the present application obtain the real-time operation data of the nuclear power plant and identify the system identification information of the source of the real-time operation data. The current target operation mode of the nuclear power plant is determined by the real-time operation data, and then the applicable target rule group is matched from multiple event rule groups constructed by the content of the technical specification through the system identification information and the target operation mode. The real-time operation data is identified as abnormal by the target rule group, and when an abnormality is found, the corresponding target event rule is triggered, and the corresponding target processing information can be obtained according to the target event rule. It can be seen that the present application constructs multiple event rule groups through the content of the technical specification, and determines the applicable target rule group based on the system identification information and the current target operation mode of the nuclear power plant, and then identifies the abnormality of the actual operation data of the nuclear power plant. When the target event rule is triggered, the corresponding target processing information is given. Thereby, the efficient use of the technical specification is achieved.

[0208] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0209] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0210] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0211] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0212] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0213] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0214] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0215] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0216] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0217] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0218] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. An abnormality handling method based on a nuclear power plant technical specification, characterized in that: The method comprises: Acquiring real-time operation data of a nuclear power plant; wherein the real-time operation data is configured with system identification information identifying a source of the data; determining a target operation mode of the nuclear power plant based on the real-time operation data; According to the system identification information and the target operation mode, matching an applicable target rule group from a plurality of preset event rule groups; wherein the event rule group is constructed according to the content of the technical specification; Based on the target rule group, the real-time operation data is identified for abnormality, and according to the triggered target event rule, the target processing information corresponding to the target event rule is obtained.

2. The method according to claim 1, characterized in that Before matching an applicable target rule group from a plurality of preset event rule groups according to the system identification information and the target operation mode, the method further includes constructing the event rule group based on a technical specification, specifically including: Perform character recognition processing on the contents recorded in the technical specification to obtain text data of the specification; Analyze the applicable scope according to the specification text data to obtain multiple rule applicable condition information; Perform rule event analysis according to the specification text data to obtain event rule data; The event rule data is grouped based on each rule applicable condition information to obtain the corresponding event rule group.

3. The method according to claim 2, characterized in that The rule event parsing is performed according to the specification document text data to obtain event rule data, including: Based on the text data of the specification, the text content is parsed to obtain the operation restriction conditions, the measure plan information, the event processing time and the abnormality inspection frequency; wherein the event processing time indicates the time reserved for solving the abnormal problem, and the abnormality inspection frequency indicates the frequency of actively inspecting the equipment or function; generating an abnormality determination condition according to the operation restriction condition; Generate an exception handling plan corresponding to the operation restriction condition according to the measure plan information; Constructing an abnormal event rule based on the abnormality determination condition, the abnormality handling solution, the event handling time, and the abnormality inspection frequency; All the abnormal event rules are integrated to obtain event rule data.

4. The method according to claim 1, characterized in that Each of the triggered target event rules will be converted into an abnormal trigger event and stored in the event record database to obtain historical event data. Based on the target rule group, the real-time operation data is identified for abnormalities, and according to the triggered target event rule, the target processing information corresponding to the target event rule is obtained, including: Based on the target rule group, determining a correlation range in the historical event data to obtain a potential correlation event group; Performing abnormality identification according to the real-time operation data, obtaining the triggered target event rule, and generating a corresponding target trigger event; Performing correlation matching in the potential correlation event group based on the target trigger event to obtain multiple target correlation events; Based on the target triggering event and the plurality of target associated events, corresponding target processing information is obtained.

5. The method according to claim 4, characterized in that Based on the target triggering event, correlation matching is performed in the potential correlation event group to obtain multiple target correlation events, including: Determine the event triggering factor and event triggering time corresponding to the target triggering event through the target event rule corresponding to the target triggering event; A plurality of associated target associated events are determined from the group of potential associated events based on the event triggering factor and the event triggering time.

6. The method according to claim 4, characterized in that Before performing correlation matching in the potential correlation event group based on the target trigger event to obtain multiple target correlation events, the method further includes constructing an event correlation network, specifically including: Obtaining the event triggering time and event triggering factor corresponding to each of the abnormal triggering events; Based on the event triggering time and the event triggering factors, a knowledge graph is constructed for each corresponding abnormal triggering event to obtain an event association network.

7. The method according to claim 4, characterized in that After obtaining corresponding target processing information based on the target triggering event and the plurality of target association events, the method further includes: According to the triggered target event rule, generating the target trigger event configured with an event priority tag, an event trigger time and an event processing time; Performing a criticality rating based on the event priority tag, the event triggering time, and the event processing time to obtain an event criticality rating of the target triggering event; Based on the event criticality rating and the plurality of target-related events, criticality rating is performed to obtain a comprehensive criticality rating; Event warning information is issued based on the comprehensive criticality rating.

8. The method according to claim 1, characterized in that: The method further includes, after identifying anomalies on the real-time operation data based on the target rule group and obtaining target processing information corresponding to the target event rule according to the triggered target event rule, evaluating the target processing information, specifically including: Based on the target processing information, an abnormality repair process is performed on the target triggering event that triggers the target event rule to obtain an abnormality repair result; Perform anomaly repair evaluation based on the anomaly repair result to obtain rule feedback information; The target event rule is iterated based on the rule feedback information to obtain a target modification rule.

9. The method according to claim 8, characterized in that The iterating the target event rule based on the rule feedback information to obtain the target modification rule includes: Perform a simulation environment test according to the target modification rule to obtain rule test information; Add the target modification rule to the target rule group according to the rule test information.

10. The method according to claim 1, characterized in that The target operation mode of the nuclear power plant is determined based on the real-time operation data, and when the nuclear power plant needs to switch the operation mode, the method further includes: Receiving an operation mode switching request and obtaining an operation mode to be switched; Based on the operation mode to be switched, matching an applicable preliminary rule group from a plurality of preset event rule groups; Performing an abnormal correlation evaluation based on the preliminary rule group and the triggered target event rule to obtain a mode switching suggestion; The operation mode switching request is executed according to the mode switching suggestion.

11. The method according to claim 10, characterized in that The abnormal correlation evaluation based on the preliminary rule group and the triggered target event rule is performed to obtain a mode switching suggestion, including: When the abnormal event rule included in the preliminary rule group is associated with the triggered target event rule, generating the mode switching suggestion that does not recommend switching the operating mode; When the abnormal event rule included in the preliminary rule group is not associated with the triggered target event rule, the mode switching suggestion for recommending switching the operation mode is generated.

12. An abnormality handling system based on a nuclear power plant technical specification, characterized in that: The system includes a data acquisition module, a rule application scope determination module, an operation mode recognition module, and an abnormality recognition and processing module; The data acquisition module is used to obtain real-time operation data of the nuclear power plant; wherein the real-time operation data is configured with system identification information identifying the source of the data; The operation mode identification module is used to determine the target operation mode of the nuclear power plant based on the real-time operation data; The rule application scope determination module is used to match an applicable target rule group from a plurality of preset event rule groups according to the system identification information and the target operation mode; wherein the event rule group is constructed according to the content of the technical specification; The exception identification and processing module is used to identify exceptions on the real-time operation data based on the target rule group, and obtain target processing information corresponding to the target event rule according to the triggered target event rule.

13. The system according to claim 12, characterized in that The system also includes a rules database and an event record database; The rule database is used to store the abnormal event rules in the event rule group; The event record database is used to store abnormal trigger events converted according to the triggered target event rules, and record the event priority label, event triggering time and event processing time corresponding to the target event rules.

14. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the abnormality handling method based on the nuclear power plant technical specification according to any one of claims 1 to 11 when executing the computer program.

15. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the abnormality handling method based on the technical specification of a nuclear power plant according to any one of claims 1 to 11 is implemented.

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