Fault diagnosis of transmission circuit based on triangular interval valued fuzzy spike neural network P system

Energy Reports

Anna Wang¹  Nan Zhou² 

[1] College of Information and Engineering, Northeastern University, Shenyang 110819, China;Corresponding author.;

关键词: Fault diagnosis;    Triangular interval value fuzzy number;    Fuzzy inference impulse neural network system;    Confidence level;    Relative preference relationship;   

DOI  :  

来源: DOAJ

【 摘 要 】

A fault diagnosis method based on fuzzy inference neural network is proposed, which can improve the uncertainty and incomplete fault information of the power system. In order to solve this problem, the IVTFSNP system is proposed. By modeling the fault area, an algebraic fuzzy inference algorithm is introduced to determine the confidence level of the candidate fault area, and the confidence level is compared with the set threshold to determine whether the area is faulty. For systems with multiple failures, further determine the probability of each failure. Several case studies have proved the accuracy and effectiveness of this method.

【 授权许可】

Unknown