CN-115438982-B - Nuclear power equipment value chain manufacturing risk assessment method

CN115438982BCN 115438982 BCN115438982 BCN 115438982BCN-115438982-B

Abstract

The invention discloses a manufacturing risk assessment method for a value chain of nuclear power equipment. The method comprises the steps of determining risk groups and risk factors in nuclear power equipment manufacturing from a risk database, defining a group of risk level assessment language sets by adopting a hesitation fuzzy language term set method, defining a semantic function as a conversion standard, acquiring assessment information of each nuclear power equipment value chain manufacturing risk factor from the risk database according to the risk groups, the risk factors and the risk level assessment language sets, converting the assessment information into triangular fuzzy numbers, aggregating, determining risk importance and risk levels of each risk factor and the risk groups, and determining overall risk importance and risk levels. The invention effectively and accurately processes fuzzy information in risk assessment, comprehensively analyzes the risk importance of each risk factor and risk group, and provides a systematic method for developing the risk assessment of the value chain manufacturing of nuclear power equipment.

Inventors

FENG YIXIONG
Hong Longzhuang
HU BINGTAO
HONG ZHAOXI
ZHANG ZHIFENG
TAN JIANRONG

Assignees

浙江大学
浙江大学

Dates

Publication Date: 20260421
Application Date: 20220915
Priority Date: 20220915

Claims (5)

1. The nuclear power equipment value chain manufacturing risk assessment method is characterized by comprising the following steps of: 1) Determining three dimensional evaluation data corresponding to each risk factor in the nuclear power equipment manufacturing according to a risk database of the nuclear power equipment, wherein the three dimensional evaluation data comprise occurrence probability evaluation data, influence degree evaluation data and uncontrollable degree evaluation data, each risk factor forms different risk groups, and a risk list is constructed by the risk groups and the risk factors; 2) Respectively carrying out fuzzy processing on occurrence probability evaluation data, influence degree evaluation data and uncontrollable degree evaluation data corresponding to each risk factor by adopting a hesitation fuzzy language term set method, respectively obtaining occurrence probability, influence degree evaluation value and uncontrollable degree evaluation value corresponding to each risk factor, calculating geometric average values of the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk factor, obtaining risk importance evaluation values of each risk factor, and converting the risk importance evaluation values of each risk factor into a risk grade evaluation language value according to a semantic function and taking the risk importance evaluation values as final evaluation values of each risk factor; 3) According to the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk factor, the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk group are calculated and obtained, and then the geometric average value of the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk group is calculated to obtain the risk importance evaluation value of each risk group, so that the final evaluation value of each risk group is determined; 4) And calculating and obtaining an occurrence probability evaluation value, an influence degree evaluation value and an uncontrollable degree evaluation value corresponding to the overall risk according to the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk group, calculating geometrical average values of the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to the overall risk, and obtaining a risk importance evaluation value of the overall risk, so as to determine a final evaluation value of the overall risk, and taking the final evaluation value of each risk factor, the final evaluation value of each risk group and the final evaluation value of the overall risk together as a risk evaluation result.
2. The method for evaluating the manufacturing risk of the value chain of the nuclear power equipment according to claim 1 is characterized in that in the step 2), three dimensional evaluation data corresponding to each risk factor are subjected to fuzzy number conversion respectively to obtain three dimensional triangular fuzzy numbers corresponding to each risk factor, one or more risk level evaluation language values exist in each dimensional evaluation data corresponding to each risk factor, when only one risk level evaluation language value exists in each dimensional evaluation data, the evaluation value corresponding to the current dimension is the triangular fuzzy number corresponding to the current dimension, and when a plurality of risk level evaluation language values exist in each dimensional evaluation data, the triangular fuzzy number obtained by weighting and summing the triangular fuzzy numbers corresponding to the current dimension is used as the evaluation value corresponding to the current dimension.
3. The method for evaluating the manufacturing risk of the value chain of the nuclear power equipment according to claim 1, wherein in the step 3), the weight of the risk factor corresponding to each risk group is calculated according to a risk list, and the calculation formula is as follows: Wherein W PO-i is the weight of the occurrence probability of the ith risk factor in the corresponding risk group, i is the risk factor number, k is the minimum number of the current group of the risk factors, l is the maximum number of the current group of the risk factors, W MI-i is the weight of the influence degree of the ith risk factor in the risk group, W UL-i is the weight of the uncontrollable degree of the ith risk factor in the risk group, T PO-i is the occurrence probability evaluation value of the ith risk factor, T MI-i is the influence degree evaluation value of the ith risk factor, and T UL-i is the uncontrollable degree evaluation value of the ith risk factor; According to the weight of the risk factors corresponding to each risk group and the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk factor, the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value of each risk group are calculated according to the following calculation formula: Wherein T ' PO-j is the occurrence probability evaluation value of the jth risk group, j is the risk group number, T ' MI-j is the influence degree evaluation value of the jth risk group, and T ' UL-j is the uncontrollable degree evaluation value of the jth risk group.
4. The method for evaluating the manufacturing risk of the value chain of the nuclear power equipment according to claim 1, wherein in the step 4), the weight of each risk group in the overall risk is calculated according to the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk group, and the calculation formula is as follows: wherein W ' PO-j is the weight of the occurrence probability of the jth risk group in the overall risk, r is the minimum number of the risk group, s is the maximum number of the risk group, W ' MI-j is the weight of the influence degree of the jth risk group in the overall risk, and W ' UL-j is the weight of the uncontrollable degree of the jth risk group in the overall risk; According to the weight of each risk group in the overall risk, calculating an occurrence probability evaluation value, an influence degree evaluation value and an uncontrollable degree evaluation value of the overall risk, wherein the formula is as follows: Wherein T ' PO-all is an occurrence probability evaluation value of the overall risk, T ' MI-all is an influence degree evaluation value of the overall risk, and T ' UL-all is an uncontrollable degree evaluation value of the overall risk.
5. The method for evaluating the manufacturing risk of the value chain of the nuclear power equipment according to claim 2 is characterized in that when two risk level evaluation language values exist in each dimension evaluation data, the weights of the triangular blur numbers corresponding to the current dimension are set to be 0.5 and 0.5 according to the sequence of the risk level evaluation language values, and when three risk level evaluation language values exist in each dimension evaluation data, the weights of the triangular blur numbers corresponding to the current dimension are set to be 0.25, 0.5 and 0.25 according to the sequence of the risk level evaluation language values.

Description

Nuclear power equipment value chain manufacturing risk assessment method Technical Field The invention relates to a value chain manufacturing risk assessment method, in particular to a nuclear power equipment value chain manufacturing risk assessment method. Background The global environmental problems are becoming more serious today, and energy structures are evolving towards clean and low carbonization. Nuclear power is a clean and efficient energy source, and the development of nuclear power has become an important national strategy in China. In the process of promoting the innovative development, the safe development and the scientific development of the nuclear power, the manufacturing industry of the nuclear power equipment faces the manufacturing risk of the value chain with diversified sources, the related risk assessment research is less, the guidance of the value chain manufacturing risk assessment theory is lacking, the value chain manufacturing risk management system of the nuclear power equipment is still immature, and the domestic and foreign case experience can be used as a reference to be less. The fuzzy linguistic approach is one solution in risk assessment, but in traditional linguistic decision frameworks, the representation of linguistic information is very limited because the information must be represented in predefined terms. The hesitant fuzzy language term set (hesitant fuzzy linguistic term set, HFLTS) method allows multiple sequential terms to be used simultaneously, conforms to the uncertainty and hesitation in human language assessment, and can improve the accuracy of risk assessment. The fuzzy comprehensive evaluation is a method for comprehensively evaluating the membership degree of an evaluated object from a plurality of factors by using a fuzzy relation comprehensive principle to quantify some factors with unclear boundaries and non-quantification based on fuzzy mathematics. The membership theory can convert qualitative evaluation into quantitative evaluation, has strong practicability on various nondeterminacy problems, has the advantages of clear results and strong systematicness, and can solve the problems of ambiguity and difficult quantification. In conclusion, the method for effectively evaluating the importance of the manufacturing risk of the value chain of the nuclear power equipment is very significant. Disclosure of Invention Aiming at the problems, the invention provides a nuclear power equipment value chain manufacturing risk assessment method, which comprises the steps of determining risk groups and risk factors in nuclear power equipment manufacturing from a risk database, defining a group of risk level assessment language sets based on hesitant fuzzy language term sets, defining semantic functions as conversion standards, acquiring assessment information of each nuclear power equipment value chain manufacturing risk factor from the risk database according to the risk groups, the risk factors and the risk level assessment language sets, converting the assessment information into triangular fuzzy numbers, aggregating, determining risk importance and risk levels of each risk factor and the risk groups, and determining overall risk importance and risk levels. The specific technical scheme of the invention is as follows: 1) Determining three dimensional evaluation data corresponding to each risk factor in the nuclear power equipment manufacturing according to a risk database of the nuclear power equipment, wherein the three dimensional evaluation data comprise occurrence probability evaluation data, influence degree evaluation data and uncontrollable degree evaluation data, each risk factor forms different risk groups, and a risk list is constructed by the risk groups and the risk factors; 2) Respectively carrying out fuzzy processing on occurrence probability evaluation data, influence degree evaluation data and uncontrollable degree evaluation data corresponding to each risk factor by adopting a hesitation fuzzy language term set method, respectively obtaining occurrence probability, influence degree evaluation value and uncontrollable degree evaluation value corresponding to each risk factor, calculating geometric average values of the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk factor, obtaining risk importance evaluation values of each risk factor, and converting the risk importance evaluation values of each risk factor into a risk grade evaluation language value according to a semantic function and taking the risk importance evaluation values as final evaluation values of each risk factor; 3) According to the occurrence probability evaluation value, the influence degree evaluation value and the uncontrollable degree evaluation value corresponding to each risk factor, the occurrence probability evaluation value, the influence degree evaluation value a