Load evaluation method and device for nuclear power plant operation task and related equipment

Abstract

The invention provides a load evaluation method and device for a nuclear power plant operation task and related equipment, and the method comprises the steps: obtaining a preset nuclear power plant accident procedure, and constructing a meta-task database according to the nuclear power plant accident procedure; wherein the meta-task database comprises a plurality of meta-task types, meta-task time corresponding to each meta-task type and meta-task load capacity corresponding to each meta-task type; obtaining a target evaluation task, and decomposing the target evaluation task into a plurality of target evaluation sub-tasks which are executed in sequence according to the meta-task database; generating a task load evaluation result corresponding to the target evaluation task according to the meta-task types of the plurality of meta-tasks, the meta-task time corresponding to each meta-task type and the meta-task load capacity corresponding to each meta-task type; and performing graphical processing on the task load evaluation result and displaying the result. According to the embodiment of the invention, real-time evaluation and analysis can be carried out on the personnel task load in a given accident scene based on the accident handling procedure.

Description

Technical Field

[0001] This application relates to the field of nuclear power plant accident management, and particularly to a method, device and related equipment for load assessment of nuclear power plant operation tasks. Background Art

[0002] The accident handling procedures of a nuclear power plant are a set of solutions designed to respond to and handle various potential accidents. When an accident occurs at a nuclear power plant, the operator needs to perform operations step by step according to these procedures to ensure the safe state of the nuclear power plant. However, after an accident occurs at a nuclear power plant, the operator undertakes a large workload and has a heavy task load during the accident handling process according to the accident procedures. Therefore, it is necessary to analyze and evaluate their workload.

[0003] In related technologies, the methods for evaluating the workload of operators include the primary task measurement method, the secondary task measurement method, the subjective measurement method, and the physiological measurement method. The primary task measurement method indirectly measures the workload by measuring the task performance of personnel, while the secondary task measurement method may interfere with the main task; although the subjective measurement method can intuitively reflect the subjective workload of personnel, it is greatly affected by subjective factors and has low consistency and credibility; the physiological measurement method requires collecting and analyzing a large amount of data. It can be seen that the existing methods all need to evaluate the personnel task load through tests or experiments, and cannot directly obtain the load result from the task content. Summary of the Invention

[0004] This application aims to at least solve one of the technical problems existing in the prior art. For this purpose, this application provides a method, device and related equipment for load assessment of nuclear power plant operation tasks, which can perform real-time assessment and analysis of the personnel task load under a given accident scenario based on the accident handling procedures.

[0005] In a first aspect, an embodiment of this application provides a method for load assessment of nuclear power plant operation tasks, including:

[0006] Obtain a preset nuclear power plant accident procedure, and construct a meta-task database according to the nuclear power plant accident procedure; wherein, the meta-task database includes multiple meta-task types, the meta-task time corresponding to each meta-task type, and the meta-task load amount corresponding to each meta-task type;

[0007] Obtain a target assessment task, and decompose the target assessment task into multiple target assessment subtasks that are executed sequentially according to the meta-task database; wherein, each target assessment subtask includes multiple meta-tasks that are executed sequentially;

[0008] Generate a task load assessment result corresponding to the target assessment task according to the meta-task types of the multiple meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load amount corresponding to each meta-task type;

[0009] Graphically process and display the task load evaluation result.

[0010] In some embodiments, the nuclear power plant accident procedure includes operation task paths under multiple accident scenarios, and each operation task path includes multiple meta-tasks executed in sequence. Obtaining the preset nuclear power plant accident procedure and constructing a meta-task database according to the nuclear power plant accident procedure includes:

[0011] Obtain the nuclear power plant accident procedure, and classify all meta-tasks in the nuclear power plant accident procedure based on the operation type to obtain multiple meta-task types;

[0012] Obtain the meta-task prior data of each meta-task type, and calculate the corresponding meta-task time according to the meta-task prior data;

[0013] Calculate the meta-task load based on the preset multi-resource theory model and the meta-task prior data;

[0014] Construct the meta-task database according to the meta-task type, the meta-task time, and the meta-task load.

[0015] In some embodiments, calculating the meta-task load based on the preset multi-resource theory model and the meta-task prior data includes:

[0016] According to the multi-resource theory model, divide the meta-task load into a visual load component, an auditory load component, a cognitive load component, and a motor load component;

[0017] Determine the visual load component value, the auditory load component value, the cognitive load component value, and the motor load component value of each meta-task type according to the meta-task prior data;

[0018] Perform weighted summation on the visual load component value, the auditory load component value, the cognitive load component value, and the motor load component value to obtain the meta-task load corresponding to the meta-task type.

[0019] In some embodiments, determining the visual load component value, the auditory load component value, the cognitive load component value, and the motor load component value of each meta-task type according to the meta-task prior data includes:

[0020] For each meta-task type, determine the corresponding visual load component level, auditory load component level, cognitive load component level, and motor load component level according to the meta-task prior data;

[0021] Obtain the corresponding relationship between the preset load component levels and load component values, and determine the visual load component value, the auditory load component value, the cognitive load component value, and the motor load component value according to the corresponding relationship.

[0022] In some embodiments, the obtaining the target evaluation task and decomposing the target evaluation task into a plurality of target evaluation subtasks to be executed sequentially according to the meta-task database includes:

[0023] Obtain the target evaluation task and the accident scenario corresponding to the target evaluation task;

[0024] According to the accident scenario, determine the operation task path corresponding to the target evaluation task in the preset nuclear power plant accident procedures; wherein, the operation task path includes a plurality of target evaluation subtasks to be executed sequentially, and each target evaluation subtask includes a plurality of meta-tasks to be executed sequentially;

[0025] For each meta-task, compare the meta-task with a plurality of meta-task types in the meta-task database, and determine the target meta-task type that matches the meta-task from the plurality of meta-task types.

[0026] In some embodiments, the generating the task load evaluation result corresponding to the target evaluation task according to the meta-task types of the plurality of meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load amount corresponding to each meta-task type includes:

[0027] For each meta-task in each target evaluation subtask, obtain the corresponding target meta-task time and target meta-task load amount from the meta-task database according to the corresponding target meta-task type;

[0028] For each target evaluation subtask, accumulate the target meta-task times corresponding to the plurality of meta-tasks in the target evaluation subtask to obtain the corresponding subtask time;

[0029] Accumulate the subtask times of the plurality of target evaluation subtasks to obtain the total task completion time of the target evaluation task, and use the total task completion time as the time axis;

[0030] For each target evaluation subtask, perform a weighted sum of the target meta-task load amounts corresponding to the plurality of meta-tasks in the target evaluation subtask to obtain the corresponding subtask load;

[0031] Based on the subtask loads of the plurality of target evaluation subtasks, determine the task loads of each time period of the target evaluation task, and map the task loads of each time period of the target evaluation task to the time axis to obtain the task load distribution;

[0032] Generate the task load evaluation result based on the total task completion time and the task load distribution.

[0033] In some embodiments, the graphical processing and display of the task load evaluation result includes:

[0034] Obtain a preset first load threshold and a second load threshold; wherein, the first threshold is less than the second threshold;

[0035] Compare the task load in each time period of the task load evaluation result with the first threshold and the second threshold:

[0036] When the task load is less than the first threshold, determine that the task load level in this time period is the low load level;

[0037] When the task load is greater than or equal to the first threshold and less than the second threshold, determine that the task load level in this time period is the medium load level;

[0038] When the task load is greater than or equal to the second threshold, determine that the task load level in this time period is the high load level;

[0039] Based on the task load levels in each time period, draw a task load distribution diagram; wherein, the low load level, the medium load level and the high load level are identified with different colors.

[0040] In some embodiments, after obtaining a preset nuclear power plant accident procedure and constructing a meta-task database according to the nuclear power plant accident procedure, the method further includes:

[0041] In response to detecting the occurrence of a sudden accident, determine the accident handling path corresponding to the sudden accident according to the nuclear power plant accident procedure; wherein, the accident handling path includes a plurality of target subtasks to be executed in sequence, and each of the target subtasks includes a plurality of meta-tasks to be executed in sequence;

[0042] Send the accident handling path to a target operation object, so that the target operation object sequentially executes a plurality of the meta-tasks according to the accident handling path;

[0043] Real-time obtain the task completion time of the target operation object for completing each of the meta-tasks, and generate a real-time load evaluation result of the target operation object for handling the sudden accident according to the task completion time of the target operation object for completing each of the meta-tasks and the meta-task load amount corresponding to each of the meta-tasks;

[0044] Perform image processing and display on the real-time load evaluation result.

[0045] In some embodiments, in response to detecting the occurrence of an emergency, determining an accident handling path corresponding to the emergency according to the nuclear power plant accident procedure includes:

[0046] Obtaining a plurality of accident scenarios preset in the nuclear power plant accident procedure and accident handling paths corresponding to each accident scenario;

[0047] Obtaining accident status information of the emergency, and determining an accident scenario corresponding to the emergency according to the accident status information;

[0048] Determining a corresponding accident handling path from a plurality of preset accident handling paths according to the accident scenario; wherein, the accident handling path includes a plurality of target subtasks that need to be sequentially executed to handle the emergency.

[0049] In some embodiments, obtaining in real time the task completion time of the target operation object for completing each meta-task, and generating a real-time load assessment result of the target operation object for handling the emergency according to the task completion time of the target operation object for completing each meta-task and the meta-task load corresponding to each meta-task includes:

[0050] Obtaining in real time the task completion time of each meta-task of each target subtask executed by the target operation object;

[0051] According to the meta-task type of each meta-task, obtaining the corresponding meta-task load in a preset meta-task database;

[0052] Generating a real-time load of each target subtask based on the meta-task load of each meta-task and the task completion time of each meta-task;

[0053] Synthesizing the real-time loads of the multiple target subtasks in the accident handling path in chronological order to generate a real-time load assessment result of the target operation object for handling the emergency.

[0054] In a second aspect, an embodiment of the present application provides a load assessment device based on a nuclear power plant accident procedure, including:

[0055] A first acquisition module, which acquires a preset nuclear power plant accident procedure and constructs a meta-task database according to the nuclear power plant accident procedure; wherein, the meta-task database includes a plurality of meta-task types, meta-task times corresponding to each meta-task type, and meta-task loads corresponding to each meta-task type;

[0056] A second acquisition module that acquires a target evaluation task and decomposes the target evaluation task into multiple target evaluation subtasks that are executed sequentially according to the meta-task database; wherein each of the target evaluation subtasks includes multiple meta-tasks that are executed sequentially.

[0057] A generation module that generates a task load evaluation result corresponding to the target evaluation task according to the meta-task types of multiple meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type.

[0058] A graphical module that graphically processes and displays the task load evaluation result.

[0059] An embodiment of the present application provides an electronic device, including: a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the load evaluation method for nuclear power plant operation tasks as described in any one of the embodiments of the first aspect of the present application.

[0060] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium. The storage medium stores a program, and when the program is executed by a processor, it implements the load evaluation method for nuclear power plant operation tasks as described in any one of the embodiments of the first aspect of the present application.

[0061] The load evaluation method for nuclear power plant operation tasks according to the embodiments of the present application has at least the following beneficial effects:

[0062] The load evaluation method for nuclear power plant operation tasks according to the embodiments of the present application includes: acquiring a preset nuclear power plant accident procedure and constructing a meta-task database according to the nuclear power plant accident procedure; wherein the meta-task database includes multiple meta-task types, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type; acquiring a target evaluation task and decomposing the target evaluation task into multiple target evaluation subtasks that are executed sequentially according to the meta-task database; wherein each of the target evaluation subtasks includes multiple meta-tasks that are executed sequentially; generating a task load evaluation result corresponding to the target evaluation task according to the meta-task types of multiple meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type; and graphically processing and displaying the task load evaluation result.

[0063] This application obtains a preset nuclear power plant accident procedure, constructs a meta-task database according to the nuclear power plant accident procedure. The meta-task database includes multiple meta-task types, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type, which can standardize and structurally store the basic data required for task load assessment. Then, by obtaining a target assessment task and decomposing the target assessment task into multiple sequentially executed target assessment subtasks according to the meta-task database, where each target assessment subtask includes multiple sequentially executed meta-tasks, complex operation tasks can be systematically and hierarchically decomposed to the most basic meta-task level. Next, by generating a task load assessment result corresponding to the target assessment task according to the meta-task types of multiple meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type, the task load can be quantified at the meta-task level, and the load assessment results of subtasks and the overall task can be obtained through methods such as time weighting, fully considering the load contribution and timing relationship of each stage of the task. Finally, by graphically processing and displaying the task load assessment result, the load levels and distribution of each stage of the task can be intuitively and vividly displayed, facilitating operators and managers to quickly understand and master the task load status, promptly discover problems such as excessive load or uneven distribution, and provide intuitive auxiliary decision-making information for personnel allocation, task optimization, emergency response, etc., improving the timeliness and effectiveness of task management. Compared with the existing method that needs to evaluate the personnel task load through tests or experiments, the method provided by the embodiment of this application does not require a large number of personnel tests or experiments, can directly start from the task content, utilize the pre-constructed meta-task database, quickly and accurately evaluate the task load, reduce the evaluation cost, and improve the evaluation efficiency.

[0064] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of the present application. Brief Description of the Drawings

[0065] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, where:

[0066] Figure 1 It is a flowchart of an optional method for evaluating the load of a nuclear power plant operation task provided by an embodiment of the present application;

[0067] Figure 2 It is another flowchart of an optional method for evaluating the load of a nuclear power plant operation task provided by an embodiment of the present application;

[0068] Figure 3 It is another flowchart of an optional method for evaluating the load of a nuclear power plant operation task provided by an embodiment of the present application;

[0069] Figure 4 Another optional flowchart of the load assessment method for nuclear power plant operation tasks provided by the embodiments of the present application;

[0070] Figure 5 Another optional flowchart of the load assessment method for nuclear power plant operation tasks provided by the embodiments of the present application;

[0071] Figure 6 Another optional flowchart of the load assessment method for nuclear power plant operation tasks provided by the embodiments of the present application;

[0072] Figure 7 Another optional flowchart of the load assessment method for nuclear power plant operation tasks provided by the embodiments of the present application;

[0073] Figure 8 A task load assessment diagram provided by the embodiments of the present application;

[0074] Figure 9 Another optional flowchart of the load assessment method for nuclear power plant operation tasks provided by the embodiments of the present application;

[0075] Figure 10 Another optional flowchart of the load assessment method for nuclear power plant operation tasks provided by the embodiments of the present application;

[0076] Figure 11 Another optional flowchart of the load assessment method for nuclear power plant operation tasks provided by the embodiments of the present application;

[0077] Figure 12 A task load real-time monitoring diagram provided by the embodiments of the present application;

[0078] Figure 13 A schematic diagram of the load assessment device based on the nuclear power plant accident procedure provided by the embodiments of the present application;

[0079] Figure 14 It is a schematic diagram of the hardware structure of the electronic device provided by the embodiments of the present application. Detailed implementation manners

[0080] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and should not be construed as a limitation to the present application.

[0081] In the description of the present application, the meaning of "several" is one or more, the meaning of "multiple" is more than two, and understandings such as "greater than", "less than", "exceeding", etc. do not include the base number, and understandings such as "above", "below", "within", etc. include the base number. If there is a description of "first" and "second", they are only used to distinguish technical features and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0082] In the description of the present application, it should be understood that for the description of directions, such as the directions or position relationships indicated by "above", "below", "left", "right", "front", "rear", etc., are based on the directions or position relationships shown in the drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the indicated device or element must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation to the present application.

[0083] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0084] In the description of the present application, it should be noted that unless otherwise clearly defined, words such as "set", "installed", "connected", etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present application in combination with the specific content of the technical solution. In addition, the identification of specific steps hereinafter does not represent a limitation on the step sequence and execution logic. The execution sequence and execution logic between each step should be understood and inferred with reference to the content described in the embodiment.

[0085] As a complex social-technical system, the safe operation of a nuclear power plant is of vital importance. The accident handling procedure system of a nuclear power plant is a set of solutions designed to respond to and handle various potential accidents, including unit status diagnosis, accident procedure selection, initial guidance for accident handling, various sequences of accident handling, unit status monitoring, re-guidance for accident handling, etc. When an accident occurs in a nuclear power plant, the operator needs to operate step by step according to these procedures to ensure the safe state of the nuclear power plant. During this process, the workload of the operator is very large, so an effective method is needed to analyze and evaluate the task load.

[0086] Existing workload assessment methods include the primary task measurement method, the secondary task measurement method, the subjective measurement method, and the physiological measurement method. The primary task measurement method indirectly measures workload by measuring personnel task performance. However, this method requires collecting relevant performance data of the primary task, and the process is complex. The secondary task measurement method may interfere with the main task, which is not allowed in the work of nuclear power plant operators. Although the subjective measurement method can intuitively reflect the subjective workload of personnel, it is greatly affected by subjective factors, and its consistency and credibility are low. The physiological measurement method requires collecting and analyzing a large amount of data, and there may not be a direct and simple connection between the workload of operators and their physiological responses. In addition, these methods all need to measure the personnel task load through tests or experiments, and cannot directly obtain the load result from the task content.

[0087] Therefore, in order to improve the efficiency and accuracy of workload assessment for nuclear power plant operators during accident handling, it is necessary to develop a new technical solution that can predict and evaluate the personnel task load after an accident based on the nuclear power plant accident procedures, and display and give early warnings for the personnel task load after an accident in real time.

[0088] Based on this, the present application obtains a preset nuclear power plant accident procedure and constructs a meta-task database according to the nuclear power plant accident procedure. The meta-task database includes multiple meta-task types, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type, which can standardize and structurally store the basic data required for task load assessment. Then, by obtaining a target assessment task and decomposing the target assessment task into multiple sequentially executed target assessment subtasks according to the meta-task database, where each target assessment subtask includes multiple sequentially executed meta-tasks, complex operation tasks can be systematically and hierarchically decomposed to the most basic meta-task level. Next, by generating a task load assessment result corresponding to the target assessment task according to the meta-task types of multiple meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type, the task load can be quantified at the meta-task level, and the load assessment results of subtasks and the overall task can be obtained through methods such as time weighting, fully considering the load contribution and timing relationship of each stage of the task. Finally, by graphically processing and displaying the task load assessment result, the load levels and distribution of each stage of the task can be intuitively and vividly displayed, facilitating operators and managers to quickly understand and master the task load situation, promptly discover problems such as excessive load or uneven distribution, and provide intuitive auxiliary decision-making information for personnel allocation, task optimization, emergency response, etc., improving the timeliness and effectiveness of task management. Compared with the existing method that needs to evaluate the personnel task load through tests or experiments, the method provided by the embodiment of the present application does not require a large number of personnel tests or experiments, can directly start from the task content, utilize the pre-constructed meta-task database, quickly and accurately evaluate the task load, reduce the evaluation cost, and improve the evaluation efficiency.

[0089] Please refer to Figure 1 , a method for evaluating the load of nuclear power plant operation tasks provided by an embodiment of the present invention may include, but is not limited to, the following steps 101 to step 104:

[0090] Step 101, obtain a preset nuclear power plant accident procedure and construct a meta-task database according to the nuclear power plant accident procedure;

[0091] Step 102, obtain a target assessment task and decompose the target assessment task into multiple sequentially executed target assessment subtasks according to the meta-task database;

[0092] Step 103, generate a task load assessment result corresponding to the target assessment task according to the meta-task types of multiple meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type;

[0093] Step 104, graphically process and display the task load assessment result.

[0094] In step 101 of some embodiments, it is first necessary to obtain a pre-set nuclear power plant accident procedure. A nuclear power plant accident procedure refers to a set of standardized operation processes and response measures pre-developed for various accident situations that may occur in a nuclear power plant. The accident procedure clearly stipulates the various operation tasks that operators should perform after an accident, as well as the execution sequence, time requirements, precautions, etc. of each task. By obtaining the accident procedure, all operation tasks involved in the nuclear power plant accident handling process can be comprehensively and systematically understood.

[0095] After obtaining the accident procedure, it is necessary to construct a meta-task database based on the accident procedure. The meta-task database is a structured data storage used to standardize the representation of various operation tasks included in the accident procedure. The process of constructing the meta-task database is to subdivide and refine the operation tasks in the accident procedure to form a series of most basic and indivisible operation meta-tasks, and to standardize the definition and quantitative description of the attributes of each meta-task to form a complete set of meta-task parameters.

[0096] The meta-task database mainly includes three types of key parameters: meta-task type, meta-task time, and meta-task workload. Among them, the meta-task type is used to describe the basic nature and category of a meta-task, such as monitoring type, operation type, judgment type, communication type, etc.; the meta-task time represents the standard time required to execute a meta-task, which can be obtained through statistical analysis of a large amount of historical data; the meta-task workload represents the cognitive load or work intensity borne by the operator when executing a meta-task, which can be obtained by means of subjective scoring, physiological measurement, etc.

[0097] By constructing the meta-task database, the operation tasks in the accident procedure can be formalized and structured, unifying the task description and quantitative indicators, and providing standardized data support for subsequent task decomposition and load assessment. The content of the meta-task database needs to be determined by professionals after repeated demonstration and experimental verification on the basis of fully investigating the actual operation of the nuclear power plant to ensure its rationality and reliability.

[0098] Please refer to Figure 2 , in some embodiments, the nuclear power plant accident procedure includes operation task paths under multiple accident scenarios, and each operation task path includes multiple meta-tasks executed in sequence. Step 101 may include, but is not limited to, steps 201 to 204.

[0099] Step 201, obtain the nuclear power plant accident procedure, and classify all meta-tasks in the nuclear power plant accident procedure based on the operation type to obtain multiple meta-task types;

[0100] Step 202, obtain the meta-task prior data of each meta-task type, and calculate the corresponding meta-task time according to the meta-task prior data;

[0101] Step 203, calculating the meta-task load based on the preset multi-resource theoretical model and meta-task prior data;

[0102] Step 204: construct a meta-task database according to the meta-task type, meta-task time, and meta-task load.

[0103] In step 201 of some embodiments, it is first necessary to obtain the accident procedures pre-established by the nuclear power plant. The accident procedures are standardized operating guidelines for nuclear power plants to deal with various abnormal situations and accident conditions, and stipulate a series of measures and steps that operators should take after an accident occurs. The accident procedures usually include multiple accident scenarios, each scenario corresponds to one or more operation task paths, and the paths clearly define the task items, sequence and requirements to be performed. After obtaining the accident procedures, it is necessary to comprehensively sort out and refine all the operation tasks involved in the procedures to identify the smallest granularity operation unit, that is, meta-task. Meta-task is the basic component of the task path, usually representing an independent, indivisible operation action or decision judgment, such as "start XXX pump", "close XXX valve", "check XXX parameters", etc. Each meta-task has a clear operation goal, execution condition and completion standard. After identifying all meta-tasks, it is necessary to further classify them according to the operation type of the meta-task. The specific meta-task classification rules can refer to the following table:

[0104]

[0105] Table 1

[0106] In step 202 of some embodiments, it is necessary to obtain corresponding prior data for each meta-task type, and calculate the standard execution time of the meta-task type based on the prior data. The meta-task prior data mainly includes two categories: one is historical execution data, that is, the actual execution time records of various meta-tasks in past accident handling practices; the other is expert experience data, that is, the subjective judgment and estimation of the execution time of various meta-tasks based on experience by senior operators and technical experts. Specifically, the following methods can be used to obtain and process meta-task prior data: collect historical accident reports, operation logs, monitoring records and other materials, extract the execution time data of each meta-task, and form a meta-task historical execution time data set. Then, the historical execution time data is cleaned and screened, and outliers and invalid data are eliminated to ensure the reliability and representativeness of the data. Next, the historical execution time data of each meta-task type is statistically analyzed, and descriptive indicators such as the mean, median, and standard deviation are calculated as reference values ​​for the execution time of the meta-task type.

[0107] For expert experience, it is necessary to collect the subjective judgments and estimations of experienced operators and experts on the execution times of various meta-task types to form a meta-task expert experience time dataset. Aggregate and analyze the expert experience time data for each meta-task type, and calculate the average value or weighted average value as another reference value for the execution time of this meta-task type.

[0108] Taking into comprehensive consideration the two types of data, namely historical execution time and expert experience time, perform a final estimation of the execution time for each meta-task type. Methods such as simple average and weighted average can be adopted to obtain the standard execution time value of the meta-task type. It should be noted that the calculation of meta-task time should make full use of multi-source heterogeneous prior data as much as possible, taking into account both the objectivity and subjectivity of the data to improve the reliability and accuracy of the estimation results. At the same time, the timeliness and representativeness of the prior data should also be considered. For older or less data, a lower weight can be assigned to reflect the dynamic change characteristics of the meta-task execution time.

[0109] Exemplarily, the meta-task time of each calculated meta-task is shown in the following table:

[0110] ID Meta-task Task Completion Time (min) A Invocation Procedure 0.2 B Indoor AC in Control Room 0.2 C Issuing Commands to the Site 1 D Reading Instructions 0.2 E Reading Parameters / Status 0.2 F Parameter Comparison (Simple) 0.2 G Parameter Comparison (Complex) 0.5 H Decision Making, Judgment (Simple) 0.2 I Decision Making, Judgment (Complex) 0.5 J Calculation 0.2 K Simple Operation 0.3 L Complex Operation 0.7 M Recording 0.3 N Locating / Identifying Alarm Sound 1.3

[0111] Table 2

[0112] In step 203 of some embodiments, it is necessary to quantitatively calculate and evaluate the execution load of each meta-task type by using the multi-resource theory model and meta-task prior data. The meta-task load amount refers to the comprehensive load level that an operator bears in terms of cognition, physiology, psychology, etc. when executing a certain type of meta-task, reflecting the requirements and influence degree of the meta-task on personnel. Accurately evaluating the meta-task load amount is of great significance for optimizing task design, rationally allocating human resources, and improving human-machine ergonomics.

[0113] The multi-resource theory is a cognitive load model in the field of human factors engineering. This theory holds that a person's information processing ability depends on multiple independent cognitive resources, such as perception, central processing, response output, etc., and each resource has its capacity limit. When multiple tasks simultaneously occupy the same resource, resource conflicts and interferences will occur, resulting in an increase in cognitive load and a decrease in task performance. Therefore, reasonably designing and allocating tasks so that they occupy different cognitive resources can reduce the overall load and improve task execution efficiency.

[0114] With the multi-resource theory model, the load characteristics of meta-task types can be analyzed and characterized from dimensions such as perception, cognitive processing, and response output. Specifically, key factors related to cognitive load can be extracted from the prior data of meta-tasks, such as the perceptual channels of the tasks (visual, auditory), information encoding methods (semantic, spatial), processing stages (perception, decision-making, action), degree of resource conflict, etc. Based on this, a multi-dimensional qualitative assessment of the meta-task types can be carried out, such as judging which cognitive resources are mainly occupied by the meta-tasks, whether there are resource bottlenecks and conflicts, etc., and then the meta-task load can be evaluated.

[0115] Please refer to Figure 3 , in some embodiments, step 203 may include, but is not limited to, steps 301 to 303.

[0116] Step 301, according to the multi-resource theory model, divide the meta-task load into a visual load component, an auditory load component, a cognitive load component, and a motor load component;

[0117] Step 302, according to the prior data of the meta-task, determine the visual load component value, auditory load component value, cognitive load component value, and motor load component value of each meta-task type;

[0118] Step 303, perform a weighted sum of the visual load component value, auditory load component value, cognitive load component value, and motor load component value to obtain the meta-task load corresponding to the meta-task type.

[0119] In step 301 of some embodiments, the multi-resource theory model is applied to divide the load of each meta-task type into four main components: a visual load component, an auditory load component, a cognitive load component, and a motor load component. This subdivision helps to more accurately evaluate the various resource requirements of the operator when performing each meta-task.

[0120] In step 302 of some embodiments, the prior data of the meta-task is used to determine the specific load component values of each meta-task type in terms of vision, audition, cognition, and motion. These data may be sourced from historical operation records, expert evaluations, or simulation experiments. By analyzing these data, specific load component values can be assigned to each meta-task type, which reflect the resource requirements of the operator in various aspects when performing the task.

[0121] Please refer to Figure 4 , in some embodiments, step 302 may include, but is not limited to, steps 401 to 402.

[0122] Step 401, for each meta-task type, according to the prior data of the meta-task, determine the corresponding visual load component level, auditory load component level, cognitive load component level, and motor load component level.

[0123] Step 402: Obtain the correspondence between the preset load component levels and load component values, and determine the visual load component value, auditory load component value, cognitive load component value, and motor load component value according to the correspondence.

[0124] In step 401 of some embodiments, for each meta-task type, the existing meta-task prior data is used to determine its load component levels in the four aspects of vision, audition, cognition, and motion. This prior data may be sourced from historical operation records, expert evaluations, or simulation experiments. For example, if a meta-task involves complex visual recognition, its visual load component level may be relatively high; if it involves complex decision-making, its cognitive load component level may be relatively high. By analyzing this prior data, a load component level can be assigned to each meta-task type on each channel, thus providing a basis for subsequent load calculation.

[0125] In step 402 of some embodiments, according to the correspondence between the preset load component levels and load component values, the load component levels determined in step 401 are converted into specific load component values. This correspondence may be derived based on the multi-resource theory model and experimental data, which defines the specific load values corresponding to different load component levels.

[0126] Exemplarily, referring to Table 3, if the visual load component level of a meta-task is "visual inspection and verification", the corresponding load value may be 4.0; if the auditory load component level is "determining the direction of the sound", the corresponding load value may be 4.2. In this way, specific load component values can be determined for each meta-task type on each channel.

[0127]

[0128]

[0129]

[0130] Table 3

[0131] In step 303 of some embodiments, the visual, auditory, cognitive, and motor load component values of each meta-task type are summed with weights to calculate the total load of the meta-task type. The weighted summation takes into account the different degrees of contribution of different load components to the overall workload. For example, cognitive load may be more important than visual or auditory load in certain tasks. In this way, a comprehensive meta-task load can be obtained, which more comprehensively reflects the workload on the operator when performing each meta-task type.

[0132] Through steps 301 to 303, a detailed workload assessment can be provided for each meta-task type in the nuclear power plant accident procedure. This assessment includes not only the overall workload but also the individual components of the workload. Such a breakdown and weighted summation method helps to more accurately predict and evaluate the workload of operators in accident situations, thereby improving the safety and efficiency of nuclear power plants.

[0133] Exemplarily, the table of visual workload component values (V), auditory workload component values (A), cognitive workload component values (C), and motor workload component values (P) for various meta-tasks is shown in Table 4 below:

[0134]

[0135]

[0136] Table 4

[0137] In step 204 of some embodiments, based on the collected meta-task type, meta-task time, and meta-task workload data, a meta-task database is constructed. In subsequent steps, this database will be used to generate task workload assessment results and perform real-time display and warning.

[0138] Through steps 201 to 204, a detailed meta-task database can be established for each operation task path in the nuclear power plant accident procedure. This database includes not only the execution time of each meta-task but also the workload information required to complete the meta-task. Such a database can evaluate and optimize the workload of nuclear power plant operators in accident situations, which helps to improve the safety and efficiency of nuclear power plants.

[0139] In step 102 of some embodiments, first, the specific task for which workload assessment is to be performed is determined, i.e., the target assessment task. This may be a specific operation sequence in the nuclear power plant accident procedure or a series of operations that an operator needs to perform in a specific accident scenario. Then, using the meta-task database constructed in step 101, the target assessment task is decomposed into multiple subtasks, which are executed sequentially. Each subtask represents an operation step or stage in the target assessment task. For example, if the target assessment task is "accident diagnosis", the subtasks may include "reading parameters / status", "parameter comparison", "decision-making, judgment", etc. Each subtask is further decomposed into multiple meta-tasks, which are the basic operation units that make up the subtask. For example, the subtask "reading parameters / status" may be further decomposed into meta-tasks "locating the parameter position" and "reading the device status or parameter value". This decomposition allows for a detailed workload assessment of the meta-tasks in each subtask.

[0140] Please refer to Figure 5, in some embodiments, step 102 may include, but is not limited to, steps 501 to 503.

[0141] Step 501, obtain a target evaluation task and an accident scenario corresponding to the target evaluation task;

[0142] Step 502, according to the accident scenario, determine an operation task path corresponding to the target evaluation task in a preset nuclear power plant accident procedure;

[0143] Step 503, for each sub-task, compare the sub-task with multiple sub-task types in a sub-task database, and determine a target sub-task type that matches the sub-task from the multiple sub-task types.

[0144] In step 501 of some embodiments, it is first necessary to determine a specific target evaluation task, which generally refers to a task to be performed under a specific accident scenario. The accident scenario is a description of various emergency situations that a nuclear power plant may encounter, and it provides the context for the evaluation task. The target evaluation task may be a complex operation sequence that needs to be determined according to the specific requirements of the accident scenario. This step is fundamental because it provides the necessary information for subsequent task decomposition and load assessment.

[0145] In step 502 of some embodiments, according to the determined accident scenario, find an operation task path that matches the target evaluation task in the nuclear power plant accident procedure. These operation task paths are predefined, and they detail a series of operation steps to be performed under a specific accident scenario. Each operation step or sub-task is arranged in the execution order, and each sub-task can be further decomposed into multiple sub-tasks. These sub-tasks are the basic operation units that make up the sub-task, and they are the smallest units for load assessment.

[0146] In step 503 of some embodiments, for each sub-task in the target evaluation sub-task, it is necessary to compare it in the sub-task database to determine its type. The sub-task database contains descriptions and characteristics of various sub-task types, and this information is used to match the sub-tasks in the sub-task. Through this comparison, it can be determined which predefined sub-task type each sub-task belongs to. This step is crucial because it ensures that each sub-task can be correctly classified and associated with its corresponding load assessment parameters.

[0147] Through steps 501 to 503, the target assessment task can be systematically decomposed into a series of subtasks and meta-tasks, and the correct type can be determined for each meta-task. This detailed decomposition and classification is the basis for accurate load assessment, which allows for quantitative analysis of the load of each meta-task in subsequent steps and ultimately generates the load assessment result for the entire task. This method improves the accuracy and reliability of load assessment, thus providing strong support for the operational safety of nuclear power plants.

[0148] In step 103 of some embodiments, it is necessary to calculate the task load of the entire target assessment task based on the type of each meta-task, the corresponding meta-task time, and the meta-task load. This process involves quantitative analysis of the time and load of the meta-task to generate a comprehensive task load assessment result. This result reflects the workload that the operator may face when performing the target assessment task. This assessment result is based on the data in the meta-task database, which includes the time and load of each meta-task, and is integrated and calculated into the total load of the entire task.

[0149] Please refer to Figure 6 , in some embodiments, step 103 may include, but is not limited to, steps 601 to 606.

[0150] Step 601, for each meta-task in each target assessment subtask, obtain the corresponding target meta-task time and target meta-task load from the meta-task database according to the corresponding target meta-task type;

[0151] Step 602, for each target assessment subtask, accumulate the target meta-task times corresponding to the multiple meta-tasks in the target assessment subtask to obtain the corresponding subtask time;

[0152] Step 603, accumulate the subtask times of multiple target assessment subtasks to obtain the total task completion time of the target assessment task, and use the total task completion time as the time axis;

[0153] Step 604, for each target assessment subtask, perform a weighted sum of the target meta-task loads corresponding to the multiple meta-tasks in the target assessment subtask to obtain the corresponding subtask load;

[0154] Step 605, based on the subtask loads of multiple target assessment subtasks, determine the task load for each time period of the target assessment task, and map the task load for each time period of the target assessment task to the time axis to obtain the task load distribution;

[0155] Step 606, based on the total task completion time and the task load distribution, generate the task load assessment result.

[0156] In step 601 of some embodiments, for each meta-task in a target evaluation subtask, according to the corresponding target meta-task type it matches, the corresponding target meta-task time and target meta-task workload are retrieved from the meta-task database. The meta-task database is a data set containing various meta-task types and their corresponding times and workloads. This step ensures that the workload evaluation of each meta-task is based on accurate time and workload data.

[0157] In step 602 of some embodiments, the target meta-task times of all meta-tasks in each target evaluation subtask are accumulated to calculate the total time of each subtask, i.e., the subtask time. This is done by adding up the times of all meta-tasks in the subtask, thereby obtaining the total duration of the subtask.

[0158] In step 603 of some embodiments, the subtask times of all target evaluation subtasks are accumulated to determine the total task completion time of the entire target evaluation task. This total time represents the total duration required to complete the entire task and serves as the time axis for subsequent task workload distribution analysis.

[0159] In step 604 of some embodiments, the target meta-task workloads of the meta-tasks in each target evaluation subtask are weighted and summed to calculate the total workload of each subtask, i.e., the subtask workload. This weighted sum takes into account the contribution of each meta-task to the total workload of the subtask, thereby obtaining the total workload of the subtask.

[0160] In step 605 of some embodiments, the subtask workloads of all target evaluation subtasks are used to determine the task workloads of the entire target evaluation task at different time periods. These workload amounts are then mapped onto the time axis to show the distribution of task workloads within the total task completion time, i.e., the task workload distribution.

[0161] In step 606 of some embodiments, combining the total task completion time and the task workload distribution, a task workload evaluation result of the target evaluation task is generated. This evaluation result provides the workload situation of the task at different time points, helps to identify potential overloaded time periods, and provides a basis for task optimization and workload management of operators.

[0162] In step 104 of some embodiments, the calculated task load assessment results are graphically processed to make them more intuitive and easy to understand. This graphical display can help operators and managers better understand the distribution and changes of task load, so as to make better decisions. The graphical processing may include using different colors, charts or graphs to represent different levels of task load, such as low load, medium load and high load. This intuitive display method helps to quickly identify potential overload situations and take corresponding measures to optimize task allocation or provide necessary support to ensure the safety and efficiency of operations.

[0163] Please refer to Figure 7 , in some embodiments, step 104 may include, but is not limited to, steps 701 to 706.

[0164] Step 701, obtain a preset first load threshold and a second load threshold;

[0165] Step 702, compare the task load in each time period of the task load assessment result with the first threshold and the second threshold;

[0166] Step 703, when the task load is less than the first threshold, determine that the task load level of this time period is a low load level;

[0167] Step 704, when the task load is greater than or equal to the first threshold and less than the second threshold, determine that the task load level of this time period is a medium load level;

[0168] Step 705, when the task load is greater than or equal to the second threshold, determine that the task load level of this time period is a high load level;

[0169] Step 706, draw a task load distribution diagram based on the task load levels of each time period.

[0170] In step 701 of some embodiments, two preset load thresholds, namely the first load threshold and the second load threshold, need to be determined first. These thresholds are the criteria for evaluating the task load level and are used to classify the task load into different levels. The first load threshold can be set as the boundary for distinguishing low load and medium load, while the second load threshold is used to distinguish medium load and high load.

[0171] In step 702 of some embodiments, the task load of the target assessment task in each time period or unit time is compared with the preset first and second load thresholds. This step is to determine the task load level of each time period or unit time. By comparison, it can be identified which time periods or unit times have a lower task load and which time periods or unit times have a higher task load.

[0172] In step 703 of some embodiments, if the task load evaluation result within a certain time period or per unit time is less than the first load threshold, the task load level within that time period or per unit time is determined to be a low load level. This means that the workload of the operator is relatively low within that time period or per unit time.

[0173] In step 704 of some embodiments, if the task load evaluation result within a certain time period or per unit time is greater than or equal to the first load threshold but less than the second load threshold, the task load level within that time period or per unit time is determined to be a medium load level. This indicates that the workload of the operator is at a medium level within that time period or per unit time.

[0174] In step 705 of some embodiments, if the task load evaluation result within a certain time period or per unit time is greater than or equal to the second load threshold, the task load level within that time period or per unit time is determined to be a high load level. This means that the workload of the operator is high within that time period or per unit time, and special attention and management may be required to prevent overloading operations.

[0175] In step 706 of some embodiments, according to the task load levels of the target evaluation task in each time period or per unit time, a task load distribution map as shown in Figure 8 is drawn, where the low load level, medium load level, and high load level are identified with different colors, namely green, yellow, and red respectively. This distribution map provides an intuitive view showing the distribution of task load on the time axis. Through this chart, the operator and management personnel can quickly identify the peaks and valleys of task load, so as to better plan task execution and resource allocation.

[0176] Please refer to Figure 9 , in some embodiments, after step 101, it may further include but is not limited to steps 901 to 904.

[0177] Step 901, in response to detecting the occurrence of a sudden accident, determine the accident handling path corresponding to the sudden accident according to the nuclear power plant accident procedures;

[0178] Step 902, send the accident handling path to the target operation object, so that the target operation object sequentially executes multiple meta-tasks according to the accident handling path;

[0179] Step 903, obtain the task completion time of the target operation object for completing each meta-task in real time, and generate a real-time load evaluation result of the target operation object for handling the sudden accident according to the task completion time of the target operation object for completing each meta-task and the meta-task load amount corresponding to each meta-task;

[0180] Step 904, perform image processing on the real-time load assessment result and display it.

[0181] In step 901 of some embodiments, once a sudden accident is detected, the system will automatically determine the corresponding accident handling path according to the accident procedures of the nuclear power plant. This path details the sequence of operations required to respond to a specific accident. The accident handling path is decomposed into a series of target subtasks, and each subtask is a stage or step in the handling path. Each target subtask is further divided into multiple meta-tasks, which are the basic operation units that make up the subtask and are carried out in sequence according to the execution order.

[0182] Please refer to Figure 10 , in some embodiments, step 901 may include, but is not limited to, steps 1001 to 1003.

[0183] Step 1001, obtain a plurality of accident scenarios preset in the accident procedures of the nuclear power plant and the accident handling path corresponding to each accident scenario;

[0184] Step 1002, obtain the accident status information of the sudden accident, and determine the accident scenario corresponding to the sudden accident according to the accident status information;

[0185] Step 1003, determine the corresponding accident handling path from the preset plurality of accident handling paths according to the accident scenario.

[0186] In step 1001 of some embodiments, first obtain a plurality of accident scenarios preset in the accident procedures of the nuclear power plant and the accident handling path corresponding to each scenario. These accident scenarios are predefined and cover various emergency situations that may occur, while the corresponding accident handling paths detail the sequence of operations required in a specific accident scenario.

[0187] In step 1002 of some embodiments, when a sudden accident occurs, obtain the information about the accident status in real time. This information may include key data such as the type, location, and impact range of the accident. According to this accident status information, the preset accident scenario corresponding to the sudden accident can be determined. This step ensures that the selection of the accident handling path matches the actual accident situation.

[0188] In step 1003 of some embodiments, once the accident scenario corresponding to the sudden accident is determined, the system will select a specific path that matches this scenario from the preset plurality of accident handling paths. This selected accident handling path details the operation steps required to respond to the current accident, including a series of target subtasks that are executed in sequence, and each subtask includes a plurality of meta-tasks that are executed in sequence.

[0189] In step 902 of some embodiments, the determined accident handling path is sent to the operator or automated system responsible for task execution. The target operation object will sequentially execute the meta-tasks in each sub-task according to this path. This step ensures that the operator can act quickly and accurately in accordance with the predetermined procedures.

[0190] In step 903 of some embodiments, the time required for the operation object to complete each meta-task is monitored and recorded in real time. These data will be combined with the load of each meta-task stored in the meta-task database to generate a real-time load assessment result of the operation object's handling of the emergency accident. This assessment result reflects the workload of the operation object when performing tasks, taking into account the time required to complete the tasks and the inherent load of the tasks.

[0191] Please refer to Figure 11 , in some embodiments, step 903 may include, but is not limited to, steps 1101 to 1104.

[0192] Step 1101, obtain in real time the task completion time of each meta-task for the target operation object to execute each target sub-task.

[0193] Step 1102, according to the meta-task type of each meta-task, obtain the corresponding meta-task load in the preset meta-task database.

[0194] Step 1103, based on the meta-task load of each meta-task and the task completion time of each meta-task, generate the real-time load of each target sub-task.

[0195] Step 1104, synthesize the real-time loads of multiple target sub-tasks in the accident handling path in chronological order to generate a real-time load assessment result of the target operation object's handling of the emergency accident.

[0196] In step 1101 of some embodiments, first extract the list of meta-tasks included in each response operation task from the accident handling path. These meta-tasks are the basic units of the operation task, they are predefined, and each meta-task has corresponding preset values for load and completion time. Monitor in real time the time required for the target operation object (such as the operator of a nuclear power plant) to execute each meta-task. These data are obtained by real-time tracking of the task execution of the operation object, providing the necessary time information for subsequent load assessment. Then, according to the characteristics and requirements of each meta-task, determine the type of each meta-task. The meta-task type is an identifier in the meta-task database used to find the preset values of the load and completion time related to the meta-task.

[0197] In step 1102 of some embodiments, according to the determined meta-task types, the preset workloads for each meta-task type are retrieved from the meta-task database. These workloads are preset based on historical data and expert evaluations, reflecting the workload required to execute each meta-task.

[0198] In step 1103 of some embodiments, by combining the workload of each meta-task and the actual completion time, the real-time workload of each response operation task is calculated. This real-time workload reflects the actual workload of the operation object when executing each task, taking into account the complexity and execution speed of the task.

[0199] In step 1104 of some embodiments, the real-time workloads of all response operation tasks are synthesized in chronological order to generate an overall real-time workload assessment result for the target operation object to handle emergencies. This assessment result provides the workload distribution of the operation object during the entire accident handling process, helping to monitor and adjust the workload of the operation object in real time to ensure that it does not exceed the safety and efficiency thresholds.

[0200] Through steps 1101 to 1104, it is possible to evaluate and monitor the workload of the operation object in real time when handling emergencies, providing strong support for the safety management and operation efficiency of nuclear power plants. This method helps to ensure that the workload of the operation object is reasonably managed at critical moments, thereby improving the safety and response efficiency of nuclear power plants.

[0201] In step 904 of some embodiments, the real-time workload assessment result is processed graphically and displayed to relevant personnel in the form of graphs or charts. This visual representation enables managers and operators to quickly understand the current workload situation, identify any potential overloading risks, and take appropriate measures to adjust task execution or provide necessary support. As Figure 12 shown, the graphical processing may include using different colors, charts, or graphs to represent different levels of task workloads, such as low workload, medium workload, and high workload.

[0202] Please refer to Figure 13 , the embodiment of the present application also provides a load assessment device 1300 based on the accident procedures of nuclear power plants, which can implement the above load assessment method for nuclear power plant operation tasks, including:

[0203] A first acquisition module 1301, which acquires the preset accident procedures of the nuclear power plant and constructs a meta-task database according to the accident procedures of the nuclear power plant; wherein, the meta-task database includes multiple meta-task types, the meta-task time corresponding to each meta-task type, and the meta-task workload corresponding to each meta-task type;

[0204] A second acquisition module 1302 acquires a target evaluation task and decomposes the target evaluation task into a plurality of target evaluation subtasks to be executed sequentially according to a meta-task database; wherein each target evaluation subtask includes a plurality of meta-tasks to be executed sequentially.

[0205] A generation module 1303 generates a task load evaluation result corresponding to the target evaluation task according to the meta-task types of a plurality of meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type.

[0206] A graphical module 1304 performs graphical processing on the task load evaluation result and displays it.

[0207] According to the load evaluation method for nuclear power plant operation tasks in an embodiment of the present application, it includes: acquiring a preset nuclear power plant accident procedure and constructing a meta-task database according to the nuclear power plant accident procedure; wherein the meta-task database includes a plurality of meta-task types, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type; acquiring a target evaluation task and decomposing the target evaluation task into a plurality of target evaluation subtasks to be executed sequentially according to the meta-task database; wherein each target evaluation subtask includes a plurality of meta-tasks to be executed sequentially; generating a task load evaluation result corresponding to the target evaluation task according to the meta-task types of a plurality of meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type; performing graphical processing on the task load evaluation result and displaying it.

[0208] This application obtains a preset nuclear power plant accident procedure and constructs a meta-task database according to the nuclear power plant accident procedure. The meta-task database includes multiple meta-task types, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type, which can standardize and structurally store the basic data required for task load assessment. Then, by obtaining a target assessment task, the target assessment task is decomposed into multiple sequentially executed target assessment subtasks according to the meta-task database, where each target assessment subtask includes multiple sequentially executed meta-tasks, which can systematically and hierarchically decompose complex operation tasks to the most basic meta-task level. Next, by generating a task load assessment result corresponding to the target assessment task according to the meta-task types of multiple meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type, the task load can be quantified at the meta-task level, and the load assessment results of subtasks and the overall task can be obtained through methods such as time weighting, fully considering the load contribution and timing relationship of each stage of the task. Finally, by graphically processing and displaying the task load assessment result, the load levels and distributions of each stage of the task can be intuitively and vividly displayed, facilitating operators and managers to quickly understand and master the task load status, promptly discover problems such as excessive load or uneven distribution, and provide intuitive auxiliary decision-making information for personnel allocation, task optimization, emergency response, etc., improving the timeliness and effectiveness of task management. Compared with the existing method that needs to evaluate the personnel task load through tests or experiments, the method provided by the embodiment of this application does not require a large number of personnel tests or experiments, can directly start from the task content, utilize the pre-constructed meta-task database, quickly and accurately evaluate the task load, reduce the evaluation cost, and improve the evaluation efficiency.

[0209] Refer to Figure 14 , Figure 14 Figure 7 illustrates the hardware structure of an electronic device according to another embodiment. The electronic device includes:

[0210] A processor 1401, which can be implemented by using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided by the embodiments of this application;

[0211] The memory 1402 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), etc. The memory 1402 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 1402, and the processor 1401 is used to call and execute the load assessment method for the nuclear power plant operation tasks in the embodiments of this application;

[0212] The input / output interface 1403 is used to implement information input and output;

[0213] The communication interface 1404 is used to implement communication and interaction between this device and other devices. It can achieve communication through a wired manner (such as USB, network cable, etc.), or can also achieve communication through a wireless manner (such as mobile network, Wi-Fi, Bluetooth, etc.);

[0214] The bus 1405 transmits information between various components of the device (such as the processor 1401, the memory 1402, the input / output interface 1403, and the communication interface 1404);

[0215] Among them, the processor 1401, the memory 1402, the input / output interface 1403, and the communication interface 1404 achieve communication connections with each other inside the device through the bus 1405.

[0216] The embodiments of this application also provide a computer program product, which includes a computer program. The processor of the computer device reads and executes this computer program, so that the computer device executes the load assessment method for the nuclear power plant operation tasks as described above.

[0217] Terms such as "first", "second", "third", "fourth", etc. (if any) in the specification of this disclosure and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of this disclosure described here can be implemented in an order other than those illustrated or described here. In addition, the terms "include" and "contain" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0218] It should be understood that in this disclosure, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or similar expressions refer to any combination of these items, including any combination of single items (ones) or plural items (ones). For example, at least one (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.

[0219] It should be understood that in the description of the embodiments of this application, the meaning of a plurality (or multiple items) is more than two. Understandings such as greater than, less than, exceeding, etc. do not include the present number, and understandings such as above, below, within, etc. include the present number.

[0220] In several embodiments provided in this disclosure, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of devices or units can be in electrical, mechanical or other forms.

[0221] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0222] In addition, the functional units in each embodiment of this disclosure can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0223] When 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 such understanding, the technical solution of the present disclosure, in essence, 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. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0224] It should also be understood that the various embodiments provided in the embodiments of the present application can be combined arbitrarily to achieve different technical effects.

[0225] The above is a specific description of the embodiments of the present disclosure, but the present disclosure is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present disclosure, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present disclosure.

Claims

1. A load assessment method for a nuclear power plant operation task, characterized in that: include: Acquire a preset nuclear power plant accident procedure, and construct a meta-task database according to the nuclear power plant accident procedure; wherein the meta-task database includes a plurality of meta-task types, a meta-task time corresponding to each meta-task type, and a meta-task load corresponding to each meta-task type; Acquire a target evaluation task, and decompose the target evaluation task into a plurality of target evaluation subtasks to be executed sequentially according to the meta-task database; wherein each of the target evaluation subtasks includes a plurality of the meta-tasks to be executed sequentially; Generate a task load evaluation result corresponding to the target evaluation task according to the meta-task types of the plurality of meta-tasks, the meta-task time corresponding to each of the meta-task types, and the meta-task load corresponding to each of the meta-task types; The task load evaluation result is processed and displayed graphically.

2. The method according to claim 1, characterized in that The nuclear power plant accident procedure includes operation task paths under multiple accident scenarios, each of the operation task paths includes multiple meta-tasks executed in sequence, and the obtaining of a preset nuclear power plant accident procedure and the building of a meta-task database according to the nuclear power plant accident procedure include: Acquire the nuclear power plant accident procedure, and classify all meta-tasks in the nuclear power plant accident procedure based on operation types to obtain multiple meta-task types; Obtaining meta-task priori data of each meta-task type, and calculating the corresponding meta-task time according to the meta-task priori data; Calculating the meta-task load based on a preset multi-resource theoretical model and the meta-task prior data; The meta-task database is constructed according to the meta-task type, the meta-task time and the meta-task load.

3. The method according to claim 2, characterized in that The calculating the meta-task load based on the preset multi-resource theoretical model and the meta-task prior data includes: According to the multi-resource theory model, the meta-task load is divided into a visual load component, an auditory load component, a cognitive load component and a motor load component; Determining, according to the meta-task priori data, a visual load component value, an auditory load component value, a cognitive load component value, and a motor load component value of each meta-task type; The visual load component value, the auditory load component value, the cognitive load component value and the motion load component value are weightedly summed to obtain the meta-task load amount corresponding to the meta-task type.

4. The method according to claim 3, characterized in that Determining the visual load component value, auditory load component value, cognitive load component value and motion load component value of each meta-task type according to the meta-task priori data includes: For each of the meta-task types, determining the corresponding visual load component level, auditory load component level, cognitive load component level and motor load component level according to the meta-task priori data; The correspondence between the preset load component levels and the load component values ​​is obtained, and the visual load component value, the auditory load component value, the cognitive load component value, and the motion load component value are determined according to the correspondence.

5. The method according to claim 1, characterized in that The obtaining of the target evaluation task, decomposing the target evaluation task into a plurality of target evaluation subtasks to be executed sequentially according to the meta-task database, includes: Acquire the target assessment task and the accident scenario corresponding to the target assessment task; According to the accident scenario, determining an operation task path corresponding to the target assessment task in a preset nuclear power plant accident procedure; wherein the operation task path includes a plurality of target assessment subtasks executed in sequence, and each of the target assessment subtasks includes a plurality of meta-tasks executed in sequence; For each of the meta-tasks, the meta-task is compared with a plurality of meta-task types in the meta-task database, and a target meta-task type matching the meta-task is determined from the plurality of meta-task types.

6. The method according to claim 1, characterized in that The step of generating a task load evaluation result corresponding to the target evaluation task according to the meta-task types of the plurality of meta-tasks, the meta-task time corresponding to each meta-task type, and the meta-task load corresponding to each meta-task type comprises: For each of the meta-tasks in each of the target evaluation sub-tasks, according to the corresponding target meta-task type, obtaining the corresponding target meta-task time and target meta-task load from the meta-task database; For each of the target evaluation subtasks, the target meta-task times corresponding to the multiple meta-tasks in the target evaluation subtask are accumulated to obtain the corresponding subtask time; Accumulate the subtask times of the multiple target evaluation subtasks to obtain the total task completion time of the target evaluation task, and use the total task completion time as the time axis; For each of the target evaluation subtasks, weighted summing is performed on the target meta-task loads corresponding to the multiple meta-tasks in the target evaluation subtask to obtain the corresponding subtask load; Based on the subtask loads of the plurality of target evaluation subtasks, determining the task load of each time period of the target evaluation task, and mapping the task load of each time period of the target evaluation task to the time axis to obtain a task load distribution; The task load evaluation result is generated based on the total task completion time and the task load distribution.

7. The method according to claim 1, characterized in that The graphically processing and displaying the task load evaluation result includes: Obtain a preset first load threshold and a second load threshold; wherein the first threshold is less than the second threshold; Compare the task load of each time period in the task load evaluation result with the first threshold and the second threshold: When the task load is less than the first threshold, determining the task load level of the time period as a low load level; When the task load is greater than or equal to the first threshold and less than the second threshold, determining that the task load level of the time period is a medium load level; When the task load is greater than or equal to the second threshold, determining that the task load level of the time period is a high load level; Based on the task load levels in each time period, a task load distribution diagram is drawn; wherein the low load level, the medium load level and the high load level are marked with different colors.

8. The method according to claim 1, characterized in that After obtaining the preset nuclear power plant accident procedures and constructing a meta-task database according to the nuclear power plant accident procedures, the method further includes: In response to detecting the occurrence of an unexpected accident, determining an accident handling path corresponding to the unexpected accident according to the accident procedure of the nuclear power plant; wherein the accident handling path includes a plurality of target subtasks executed in sequence, and each of the target subtasks includes a plurality of metatasks executed in sequence; Sending the accident processing path to a target operation object, so that the target operation object sequentially executes the plurality of meta-tasks according to the accident processing path; Acquire in real time the task completion time of each meta-task completed by the target operation object, and generate a real-time load assessment result of the target operation object processing the emergency according to the task completion time of each meta-task completed by the target operation object and the meta-task load corresponding to each meta-task; The real-time load assessment result is processed into a graphic form and displayed.

9. The method according to claim 8, characterized in that In response to detecting the occurrence of an unexpected accident, determining an accident handling path corresponding to the unexpected accident according to the accident procedure of the nuclear power plant, including: Acquire multiple accident scenarios preset in the accident procedures of the nuclear power plant and the accident handling path corresponding to each accident scenario; Acquire the accident status information of the sudden accident, and determine the accident scene corresponding to the sudden accident according to the accident status information; According to the accident scenario, a corresponding accident handling path is determined from a plurality of preset accident handling paths; wherein the accident handling path includes a plurality of target subtasks that need to be executed in sequence to handle the sudden accident.

10. The method according to claim 8, characterized in that The step of acquiring in real time the task completion time of each meta-task completed by the target operation object, and generating a real-time load assessment result of the target operation object processing the emergency according to the task completion time of each meta-task completed by the target operation object and the meta-task load corresponding to each meta-task, comprises: Acquire in real time the task completion time of each meta-task executed by the target operation object for each target subtask; According to the meta-task type of each meta-task, obtaining a corresponding meta-task load in a preset meta-task database; Based on the meta-task load of each meta-task and the task completion time of each meta-task, generating the real-time load of each target sub-task; The real-time loads of the plurality of target subtasks in the accident handling path are synthesized in chronological order to generate a real-time load evaluation result of the target operation object handling the sudden accident.

11. A load assessment device based on nuclear power plant accident procedures, characterized in that: include: A first acquisition module acquires a preset nuclear power plant accident procedure and constructs a meta-task database according to the nuclear power plant accident procedure; wherein the meta-task database includes a plurality of meta-task types, a meta-task time corresponding to each meta-task type, and a meta-task load corresponding to each meta-task type; A second acquisition module acquires a target evaluation task, and decomposes the target evaluation task into a plurality of target evaluation subtasks executed sequentially according to the meta-task database; wherein each of the target evaluation subtasks includes a plurality of meta-tasks executed sequentially; A generating module, generating a task load evaluation result corresponding to the target evaluation task according to the meta-task types of the plurality of meta-tasks, the meta-task time corresponding to each of the meta-task types, and the meta-task load corresponding to each of the meta-task types; The graphical module processes and displays the task load evaluation result in graphical form.

12. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the load assessment method for a nuclear power plant operation task as described in any one of claims 1 to 10 is implemented.

13. A computer-readable storage medium, characterized in that: The storage medium stores a program, and the program is executed by a processor to implement the load assessment method for a nuclear power plant operation task as described in any one of claims 1 to 10.

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