HFE design verification and evaluation method and system for nuclear power plant human factors engineering

Abstract

The invention discloses a method and system for verifying and evaluating the design of human factors engineering (HFE) for a nuclear power plant, and relates to the technical field of verification and evaluation of human factors engineering. The invention is based on HFE influencing factors. On the one hand, a subjective evaluation data table is designed for each influencing factor. On the other hand, local and global evaluation methods are constructed under different categories of influencing factors to perform local and global multi-objective evaluations, thereby obtaining local evaluation results under each category indicator system and global evaluation results of all indicators under the category. According to the local or global evaluation results, the input values ​​of the HFE factor levels in the evaluation process can be traced back to discover the defects of one or some indicators and the overall design level, and timely and effective feedback, interface adjustment and optimization can be performed.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to a design verification and evaluation method and system for human factors engineering (HFE) of a nuclear power plant. Background Art

[0002] The human-machine interface (HMI) in a nuclear power plant is a crucial interface for operators to exchange information with the plant. It serves as the primary vehicle for operators to obtain information, parameters, and complete tasks. The quality of the HMI design directly impacts the reliability of HMI during plant operation. The HMI displays various parameters, procedures, and alarms, and operators use this information to perform cognitive activities such as diagnosis, decision-making, and execution. If designers fail to understand the adverse effects of digital HMI features on operators, even if they adhere to or consider human factors engineering (HFE) design guidelines during the HMI design process, they may overlook deeper safety issues or overlook the behavioral characteristics of operators in complex HMI situations. This makes it difficult to ensure that the designed HMI meets plant operational requirements. To date, no mature method has been developed to evaluate HMI reliability. Manual verification and evaluation based on HFE design guidelines is time-consuming and inefficient, hindering timely and effective feedback and optimization of the HMI. Summary of the Invention

[0003] One of the objectives of the present invention is to provide a design verification and evaluation method for human factors engineering (HFE) of a nuclear power plant, aiming to improve the efficiency of verification and evaluation so as to timely understand and improve the human-machine interface.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solution: a nuclear power plant human factors engineering (HFE) design verification and evaluation method, comprising the following steps:

[0005] Step 1: Based on various indicator sets of human-machine interface design input, human-machine interface design overview, human-machine interface human factors engineering design guidelines, human-machine system detailed design and integration, I&C and HSI degradation conditions, and HSI testing and evaluation.

[0006] Step 2: There are two optional evaluation methods: evaluation using the ergonomics evaluation form or evaluation using the evaluation method. If you choose to evaluate using the ergonomics evaluation form, proceed to step 3; if you choose to evaluate using the evaluation method, proceed to step 4.

[0007] Step 3: Design evaluation levels for all secondary indicators or primary indicators in the indicator set, and form corresponding ergonomics evaluation tables. In each ergonomics evaluation table, fill in the evaluation level for each indicator in turn according to the specific task or scenario, and then obtain the evaluation results. Based on the evaluation results, improve the indicators that have not met expectations.

[0008] Step 4: Based on the linear weighted evaluation method, construct a linear weighted multi-angle evaluation method, determine the indicator weights, give evaluation values ​​for each indicator in each indicator set according to the specific task or scenario, and then calculate the evaluation results. Then, based on the evaluation results, backtrack to obtain the performance of each indicator, and optimize or improve the indicators that did not meet expectations.

[0009] Preferably, in step three, the method of designing evaluation levels for each secondary indicator or primary indicator in all indicator sets includes adding a level column for the indicator, and listing multiple evaluation levels of the corresponding indicator in the level column.

[0010] More preferably, based on the linear weighted evaluation method, a method for constructing a linear weighted multi-angle evaluation includes: in various indicator sets, if an indicator set has multiple first-level indicators, and there are corresponding second-level indicators under the first-level indicators, in terms of evaluation, the overall performance of the entire indicator set can be evaluated, or, the second-level indicators under each first-level indicator in a certain indicator set can be locally evaluated separately.

[0011] More preferably, in the process of using the evaluation method, the level value of each indicator is the average value of multiple experts, which is defined as follows:

[0012]

[0013]

[0014] Among them, V Li (HFE design verification) represents the local evaluation result of the secondary indicators under the i-th primary indicator on the HFE design verification or the overall evaluation result when there is only the first-level indicator; V_I(x i,j ) represents the expert average value of the jth secondary indicator under i first-level indicators; M i represents the number of secondary indicators under the i-th primary indicator; w i,j represents the weight of the jth secondary indicator under the ith primary indicator; Count represents the number of people participating in the scoring; V_I(x i,j,k ) represents the specific score of the kth person or expert for the jth secondary indicator under the ith first-level indicator.

[0015] More preferably, the HFE design verification comprehensive evaluation calculation method is:

[0016]

[0017] Among them, V 综合 (HFE design verification) represents the comprehensive evaluation results of HFE design verification of nuclear power plant human factors engineering; n represents the number of first-level indicators; w i Represents the weight of the i-th first-level indicator.

[0018] More preferably, the level of each evaluation indicator in all indicator sets is divided into 4 levels: {excellent, good, fair, poor}, and the value range corresponding to each level is: {(85,100], (65,85], (45,65], (0,45)}; before the verification evaluation, the level of each evaluation indicator is first determined according to the specific scenario, and then a specific value is given to each indicator according to the level value range.

[0019] More preferably, each indicator in each indicator set is defined as an impact factor, and a combined weighting method based on game theory is used to obtain the weight of the impact factor, which includes the following steps:

[0020] (1) Random linear combination of k weight vectors;

[0021]

[0022] Among them, W c is the combined weight of the impact factor based on the basic weight set; m i represents the combination coefficient; w i is the weight of the i-th weighting method of the impact factor; k is the number of methods to obtain the impact factor weight;

[0023] (2) According to the differential properties of the matrix, the linear equation of the optimal first-order derivative of formula (4) is:

[0024]

[0025] (3) According to formula (5), we can get m k , m k The normalized expression of is as follows:

[0026]

[0027] (4) Calculate the optimal comprehensive weight of the impact factors:

[0028]

[0029] More preferably, the initial weight data is obtained through a questionnaire survey, and the weights of the influencing factors are obtained by analysis and calculation, and then the final comprehensive weights of the influencing factors are obtained based on the combined weighting method of game theory.

[0030] In addition, the present invention also provides a nuclear power plant human factors engineering (HFE) design verification and evaluation system, which includes an indicator set module for providing various indicator sets as a basis for human-machine interface design input, human-machine interface design overview, human-machine interface human factors engineering design guidelines, human-machine system detailed design and integration, I&C and HSI degradation, and HSI testing and evaluation; an evaluation method selection module for selecting a human factors engineering evaluation table or an evaluation method for evaluation; a human factors engineering evaluation table evaluation module for designing evaluation grades for each secondary indicator or primary indicator in all indicator sets and forming corresponding human factors engineering evaluation tables. In each human factors engineering evaluation table, an evaluation grade is sequentially filled in for each indicator according to a specific task or scenario, and then an evaluation result is obtained. Then, based on the evaluation result, improvements are made to indicators that do not meet expectations; and an evaluation method evaluation module for constructing a linear weighted multi-angle evaluation method based on a linear weighted evaluation method, determining indicator weights, giving evaluation values ​​for each indicator in each indicator set according to a specific task or scenario, and then calculating the evaluation results. Then, based on the evaluation results, the performance of each indicator is retrospectively obtained, and indicators that do not meet expectations are optimized or improved. The system is operated using the above-mentioned nuclear power plant human factors engineering HFE design verification and evaluation method.

[0031] Compared with the existing technology, the present invention uses various indicator sets as the basis, and uses human factors engineering evaluation table evaluation or evaluation using evaluation methods as two optional evaluation methods, which enriches the choice of verification and evaluation methods. At the same time, it also uses automated verification and evaluation methods to improve the efficiency of verification and evaluation, thereby enabling timely and effective feedback and optimization of the human-computer interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a process architecture diagram of the verification and evaluation method of the present invention;

[0033] Figure 2 This is the design evaluation process based on the linear weighting method in the embodiment. DETAILED DESCRIPTION

[0034] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and drawings. The contents mentioned in the embodiments are not intended to limit the present invention.

[0035] First, the verification and evaluation performed in this invention must be based on existing evaluation indicators. Specifically, the evaluation indicators are primarily derived from NUREG-0711.Rev.3 Human Factors Design Review Guidelines. The evaluation focuses on several aspects: human-machine interface design input, human-machine interface design overview, human-machine interface human factors design guidelines, human-machine system detailed design and integration, I&C and HSI degradation, and HSI testing and evaluation. The specific primary and secondary evaluation indicators for each category are shown in Tables 1, 2, 3, 4, 5, and 6, respectively.

[0036] Table 1 Performance evaluation indicators of “Human-machine interface design input (A)”

[0037]

[0038] Table 2 Performance evaluation indicators of “Overview of human-computer interface design (B)”

[0039]

[0040] Table 3 Performance evaluation indicators of “Human-machine interface human factors engineering design guidelines (C)”

[0041]

[0042]

[0043] Table 4 Performance evaluation indicators of “Detailed design and integration of human-machine system (D)”

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050] Table 5 Performance evaluation indicators for “I&C and HSI degradation condition (E)”

[0051]

[0052] Table 6 “HSI test and evaluation (F)” performance evaluation indicators

[0053]

[0054] There are two ways to conduct specific verification and evaluation. One way is to use the human factors engineering evaluation table. For specific tasks or scenarios, evaluate the indicators in Table 1, Table 2, Table 3, Table 4, Table 5, and Table 6 in turn. The quality of each indicator is expressed by a grade, such as (good, relatively good, average, poor). The other way is to use the evaluation method to calculate the evaluation value for Table 1 to Table 6 respectively. The performance is expressed based on the evaluation value. The score of each indicator in the evaluation process can be traced back, and the performance of the indicator can be improved according to the score of the specific indicator. The evaluation process can be as follows: Figure 1 shown.

[0055] The above-mentioned human factors engineering evaluation table evaluation method will be based on Tables 1, 2, 3, 4, 5, and 6, and the indicator level column will be added. Here, using Tables 1 and 2 as examples, the human factors engineering evaluation table after the level column is added is shown in Tables 7 and 8.

[0056] Table 7 Human Factors Engineering Evaluation Table for “Human-Machine Interface Design Input (A)” Performance Index

[0057]

[0058] Table 8 Performance evaluation indicators of “Overview of human-computer interface design (B)”

[0059]

[0060] As for another verification and evaluation method, a linear weighted multi-angle evaluation method is constructed based on the linear weighted evaluation method. That is, in Tables 1 to 6, if a table has multiple first-level indicators, and there are corresponding second-level indicators under the first-level indicators, in terms of evaluation, on the one hand, the overall performance of the entire table can be evaluated, and on the other hand, the second-level indicators under each first-level indicator in a table can be locally evaluated.

[0061] Specifically, during the HFE design verification and evaluation process, the same indicator value may come from multiple personnel or experts at the nuclear power plant. Therefore, the level value of each indicator is the average of the multiple experts. Therefore, the HFE design verification and evaluation calculation formula is defined as:

[0062]

[0063]

[0064] Among them, V Li (HFE design verification) represents the local evaluation result of the secondary indicators under the i-th primary indicator on the HFE design verification or the overall evaluation result when there is only the first-level indicator; V_I(x i,j ) represents the expert average value of the jth secondary indicator under i first-level indicators; M i represents the number of secondary indicators under the i-th primary indicator; w i,j represents the weight of the jth secondary indicator under the ith primary indicator; Count represents the number of people participating in the scoring; V_I(x i,j,k ) represents the specific score of the kth person or expert for the jth secondary indicator under the ith first-level indicator.

[0065] The calculation method for the comprehensive evaluation of HFE design verification is:

[0066]

[0067] Among them, V 综合 (HFE design verification) represents the comprehensive evaluation results of HFE design verification of nuclear power plant human factors engineering; n represents the number of first-level indicators; w i Represents the weight of the i-th first-level indicator.

[0068] As can be seen from Tables 1 to 6, the influencing factors (i.e., each indicator in each indicator set) are divided into 6 different categories. When conducting HEF design verification and evaluation, each category should be evaluated separately using a linear weighted method, rather than evaluating all the influencing factors of the 6 categories together. In this way, each category will obtain an overall evaluation result, and within each category, local evaluation results of the secondary indicators under different primary indicators can be obtained. Then, based on the evaluation results, the purpose of improving and optimizing each category and the secondary indicators within each category can be achieved.

[0069] From formulas (1), (2), and (3), it is clear that the input parameters of the linear weighted evaluation method are: the input value of the impact factor level and the weights of the first-level and second-level impact factor indicators. The following describes the methods for obtaining the input value and weight of the impact factor level.

[0070] In this embodiment, all impact factors / evaluation indicator levels are divided into four levels: {Excellent, Good, Fair, Poor}, and the corresponding value ranges for each level are {(85, 100], (65, 85], (45, 65], (0, 45)}. Before HFE design verification and evaluation, the level of each factor should be determined based on the specific scenario. Then, a specific value should be assigned to each indicator based on the level value range. Correspondingly, if the evaluation result value falls within a certain level range, the corresponding level of the evaluation result can be considered as: Excellent, Good, Fair, or Poor.

[0071] In order to improve the rationality of the weight of the impact factor, a combined weighting method based on game theory is used to obtain the weight of the impact factor. The main process of this method is as follows:

[0072] (1) Random linear combination of k weight vectors;

[0073]

[0074] Among them, W c is the combined weight of the impact factor based on the basic weight set; m i represents the combination coefficient; w i is the weight of the i-th weighting method of the impact factor; k is the number of methods to obtain the impact factor weight;

[0075] (2) According to the differential properties of the matrix, the linear equation of the optimal first-order derivative of formula (4) is:

[0076]

[0077] (3) According to formula (5), we can get m k , m k The normalized expression of is as follows:

[0078]

[0079] (4) Calculate the optimal comprehensive weight of the impact factors:

[0080]

[0081] The initial weight data was obtained through a questionnaire survey. The respondents in this example included personnel from nuclear power plants, human reliability analysis experts, and experts and scholars in the field of human factors engineering. A total of 33 questionnaires were distributed, and 31 were valid.

[0082] Based on the collected data, this embodiment first obtains the weights of the influencing factors based on the hierarchical analysis method (see the paper entitled "Application of AHP Fuzzy Comprehensive Evaluation Method in Property Service Quality Evaluation" published by Zhang Bin et al. in 2021) and the improved G2 method (see the paper entitled "Analysis of Railway Tunnel Collapse Risk Based on Variable Fuzzy Set Theory" published by Wang Jing et al. in 2021). Then, based on the combined weighting method of game theory, that is, based on formulas (4), (5), (6) and (7), the final comprehensive weight of the influencing factors is obtained by analyzing the two different influencing factor weight vectors obtained by the hierarchical analysis method and the G2 method respectively. The weights of the influencing factors for the HFE design verification of nuclear power plants are shown in Tables 9, 10, 11, 12, 13 and 14 respectively.

[0083] Table 9 “Human-machine interface design input (A)” performance evaluation index weights

[0084]

[0085] Table 10 “Human-machine interface design concept (B)” performance evaluation index weights

[0086]

[0087] Table 11 Weights of performance evaluation indicators in “Human-machine interface human factors engineering design guidelines (C)”

[0088]

[0089] Table 12 Weights of performance evaluation indicators for “Detailed design and integration of human-machine system (D)”

[0090]

[0091]

[0092] Table 13 “I&C and HSI degradation (E)” performance evaluation index weights

[0093]

[0094] Table 14 “HSI Test and Evaluation (F)” performance evaluation index weights

[0095]

[0096] In order to illustrate the linear weighted evaluation process, the performance evaluation of "human-computer interface design input (A)" and "human-computer interface design concept (B)" mentioned in Table 1 and Table 2 are taken as examples. According to the characteristics and background of the method, the evaluation process is as follows: Figure 2 The specific steps are as follows:

[0097] (1) Determine the impact factor value

[0098] Take Table 1 and Table 2 as examples to illustrate the analysis process. Figure 2 As can be seen, the indicator level is determined first, and then the specific value of the indicator is determined based on the level at the indicator location. Here, taking the steam generator heat transfer tube rupture (SGTR) process, namely, "detecting the N-16 alarm signal and entering the E-0 procedure," as an example, three experts were invited to score the corresponding HFE screen design. The results are shown in Tables 15 and 16.

[0099] Table 15 “Human-machine interface design input (A)” performance evaluation index levels and specific values

[0100]

[0101]

[0102] Table 16 “Overview of Human-Machine Interface Design (B)” performance evaluation index levels and specific values

[0103]

[0104] (2) Calculation

[0105] 1) “Human-machine interface design input (A)” HFE design verification performance evaluation

[0106] As can be seen from Table 1, the human-machine interface input has only one level of indicators, so it can only be evaluated overall. According to formula (1), the corresponding weight table 9 and factor value table 15 are:

[0107] V 人机界面设计输入(A) (HFE Design Verification)

[0108] =80.7*0.303+87.3*0.224+85*0.274+63.3*0.199=79.894

[0109] According to the level range of the result, the evaluation result is: "Good", which means the performance is good.

[0110] 2) "Overview of Human-Machine Interface Design (B)" Performance HFE Design Verification Performance Evaluation

[0111] As can be seen from Table 2, the “Human-Machine Interface Design Overview” HFE design verification can be evaluated overall and locally.

[0112] ① Local evaluation

[0113] Similarly, according to formula (1), the corresponding weight table is 10 and the factor value table is 16, then:

[0114] V 人机界面设计概述输入(B1) (HFE design verification) = 90*0.536+91.7*0.464=90.8

[0115] V 人机界面设计概述输入(B2) (HFE Design Verification)

[0116] =81.7*0.291+70*0.257+80*0.239+91.7*0.213=80.4

[0117] Judging from the evaluation results of the two first-level indicators B1 and B2, the performance is "excellent" and "good" respectively.

[0118] ② Overall evaluation

[0119] According to formula (3), the corresponding weight table is 10 and the factor value table is 16, then

[0120] V 人机界面设计概述输入(B) (HFE Design Verification)

[0121] =0.465*(90*0.536+91.7*0.464)

[0122] +0.535*(81.7*0.291+70*0.257+80*0.239+91.7*0.213)

[0123] =85.236

[0124] The overall evaluation results for the Human-Computer Interface Design Overview Input (B) indicator are at an "Excellent" level. If further improvement is needed, the scores for each indicator can be reviewed and, based on the scores, performance improvements can be made accordingly.

[0125] In order to make it easier for ordinary technicians in this field to understand the improvements of the present invention over the prior art, some drawings and descriptions of the present invention have been simplified, and the above-mentioned embodiments are preferred implementation schemes of the present invention. In addition, the present invention can also be implemented in other ways. Any obvious replacement without departing from the concept of the present technical solution is within the scope of protection of the present invention.

Claims

1. The HFE design verification and evaluation method for nuclear power plants is characterized by: The following steps are involved: Step 1: Based on various indicator sets of HMI design input, HMI design overview, HMI human factors engineering design guidelines, HMI system detailed design and integration, I&C and HSI degradation, and HSI testing and evaluation; Step 2: There are two optional evaluation methods: evaluation using the human factors evaluation form or evaluation using the evaluation method. If you choose to evaluate using the human factors evaluation form, you will proceed to step 3; if you choose to evaluate using the evaluation method, you will proceed to step 4. Step 3: Design evaluation levels for all secondary or primary indicators in the indicator set and create corresponding human factors engineering evaluation tables. Enter the evaluation level for each indicator in each human factors engineering evaluation table based on the specific task or scenario. Then, obtain the evaluation results. Based on the evaluation results, improve the indicators that do not meet expectations. Step 4: Based on the linear weighted evaluation method, a linear weighted multi-angle evaluation method is constructed to determine the indicator weights. For each indicator in each indicator set, an evaluation value is given according to the specific task or scenario. The evaluation results are then calculated. Based on the evaluation results, the performance of each indicator is then back-tested to obtain the performance of each indicator. Indicators that do not meet expectations are optimized or improved. Each indicator in each indicator set is defined as an impact factor, and the weight of the impact factor is obtained by using a combined weighting method based on game theory, which includes the following steps: (1) Random linear combination of k weight vectors; （4）； Among them, W c is the combined weight of the impact factor based on the basic weight set; m i represents the combination coefficient; w i is the weight of the i-th weighting method of the impact factor; k is the number of methods to obtain the impact factor weight; (2) According to the differential properties of the matrix, the linear equation of the optimal first-order derivative of formula (4) is: （5）； (3) According to formula (5), we can get m k , m k The normalized expression of is as follows: （6）； (4) Calculate the optimal comprehensive weight of the impact factors: （7）。 2. The method for design verification and evaluation of human factors engineering (HFE) for nuclear power plants according to claim 1, characterized in that: In step three, the method of designing evaluation levels for each secondary indicator or primary indicator in all indicator sets includes adding a level column for the indicator and listing multiple evaluation levels of the corresponding indicator in the level column.

3. The method for design verification and evaluation of human factors engineering (HFE) for nuclear power plants according to claim 1, characterized in that: Based on the linear weighted evaluation method, a method for constructing a linear weighted multi-angle evaluation includes: in various indicator sets, if an indicator set has multiple first-level indicators, and there are corresponding second-level indicators under the first-level indicators, in terms of evaluation, the overall performance of the entire indicator set can be evaluated, or the second-level indicators under each first-level indicator in a certain indicator set can be locally evaluated separately.

4. The method for design verification and evaluation of human factors engineering (HFE) for nuclear power plants according to claim 3, characterized in that: In the process of using the evaluation method, the level value of each indicator is the average value of multiple experts, which is defined as follows: （1）； （2）； Among them, V Li ( ) represents the secondary index pair under the i-th primary index The local evaluation results or the overall evaluation results when there are only first-level indicators; M represents the expert average value of the jth secondary indicator under i first-level indicators; i represents the number of secondary indicators under the i-th primary indicator; w i,j It represents the weight of the jth secondary indicator under the ith primary indicator; Count represents the number of people participating in the scoring; It represents the specific score value of the kth person or expert for the jth secondary indicator under the ith first-level indicator.

5. The method for verification and evaluation of HFE design for nuclear power plants according to claim 4, characterized in that: The calculation method for the comprehensive evaluation of HFE design verification is: （3）； in, represents the comprehensive evaluation results of HFE design verification of nuclear power plants; n represents the number of first-level indicators; w i Represents the weight of the i-th first-level indicator.

6. The method for verification and evaluation of HFE design for a nuclear power plant according to claim 5, characterized in that: The level of each evaluation indicator in the set of all indicators is divided into four levels: {Excellent, Good, Fair, Poor}, and the corresponding value range of each level is: {(85,100], (65,85], (45,65], (0,45)}; before verification and evaluation, the level of each evaluation indicator is determined according to the specific scenario, and then a specific value is given to each indicator based on the level value range.

7. The method for design verification and evaluation of human factors engineering (HFE) for a nuclear power plant according to claim 6, characterized in that: The initial weight data is obtained through questionnaire surveys, and the weights of the influencing factors are obtained through analysis and calculation. Then, the final comprehensive weights of the influencing factors are obtained by the combined weighting method based on game theory.

8. A nuclear power plant human factors engineering (HFE) design verification and evaluation system, characterized by: include: The indicator set module is used to provide various indicator sets as the basis for human-machine interface design input, human-machine interface design overview, human-machine interface human factors engineering design guidelines, human-machine system detailed design and integration, I&C and HSI degradation, and HSI testing and evaluation; Evaluation method selection module, used to select the evaluation form of human factors engineering or the evaluation method; The human factors engineering evaluation table module is used to design evaluation levels for each secondary indicator or primary indicator in the entire indicator set and form a corresponding human factors engineering evaluation table. In each human factors engineering evaluation table, the evaluation level is filled in for each indicator in turn according to the specific task or scenario, and then the evaluation results are obtained. Based on the evaluation results, improvements are made to the indicators that do not meet expectations; The evaluation method evaluation module is used to construct a linear weighted multi-angle evaluation method based on the linear weighted evaluation method, determine the indicator weights, give evaluation values ​​for each indicator in the various indicator sets according to specific tasks or scenarios, and then calculate the evaluation results. Based on the evaluation results, the performance of each indicator is obtained retrospectively, and the indicators that do not meet expectations are optimized or improved; The method for verifying and evaluating the design of human factors engineering (HFE) for a nuclear power plant according to any one of claims 1 to 7 is adopted for operation.

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