Recognition and determination of fuzzy logical relationship in the system fault evolution process
作者:
Highlights:
• The concepts of system fault evolution process and space fault network theory are proposed by the authors.
• Referring to 14 kinds of logical relationships in flexible logic, the author transforms them into the event occurrence logical relationship formula, which can be regarded as the basic logical relationships; the latter uses enumeration method to change the fuzzy membership degree, and obtains the optimal fuzzy membership degree when the fitness function is closest to 0. Finally, the concrete form of fuzzy logical structure function is obtained.
• The fuzzy logical relationship between the cause event and the result event is determined by using neural network; and the algorithm analysis diagram and steps are given. The method can effectively solve the problem of determining the fuzzy logical relationship between events in the system fault evolution process.
摘要
•The concepts of system fault evolution process and space fault network theory are proposed by the authors.•Referring to 14 kinds of logical relationships in flexible logic, the author transforms them into the event occurrence logical relationship formula, which can be regarded as the basic logical relationships; the latter uses enumeration method to change the fuzzy membership degree, and obtains the optimal fuzzy membership degree when the fitness function is closest to 0. Finally, the concrete form of fuzzy logical structure function is obtained.•The fuzzy logical relationship between the cause event and the result event is determined by using neural network; and the algorithm analysis diagram and steps are given. The method can effectively solve the problem of determining the fuzzy logical relationship between events in the system fault evolution process.
论文关键词:intelligent method,system fault evolution process,fuzzy logic,relationship recognition,fuzzy membership degree,flexible logic
论文评审过程:Received 24 January 2021, Revised 28 April 2021, Accepted 3 May 2021, Available online 26 May 2021, Version of Record 26 May 2021.
论文官网地址:https://doi.org/10.1016/j.ipm.2021.102630