Title :
Power Transformer Fault Diagnosis Based on Fuzzy Integral Fusion
Author :
Ling, Zhou ; Huimin, Yan ; Yonggang, Cao
Author_Institution :
Hohai Univ.
Abstract :
A new method to identify power transformer faults based on fuzzy integral fusion is presented. Firstly, the membership function of the value of three-ratio are presented and the data of the value of three ratios are processed by fuzzy method. Then the faults are identified by four different radial basis function (RBF) neural networks. Finally results of identification from four different neural networks are fused by fuzzy integral fusion and then form the final diagnosis. The results of simulation by presented method have been proved to be more accuracy than single neural network in identifying the practical transformer fault case
Keywords :
fault diagnosis; fuzzy set theory; power engineering computing; power transformers; radial basis function networks; RBF neural network; fault diagnosis; fuzzy integral fusion; membership function; power transformer; radial basis function; Agriculture; Dissolved gas analysis; Electrical equipment industry; Equations; Fault diagnosis; Fuzzy neural networks; Fuzzy systems; Hydrogen; Neural networks; Power transformers; fault diagnosis; fuzzy integral; power transformer; radial basis function (RBF);
Conference_Titel :
Universities Power Engineering Conference, 2006. UPEC '06. Proceedings of the 41st International
Conference_Location :
Newcastle-upon-Tyne
Print_ISBN :
978-186135-342-9
DOI :
10.1109/UPEC.2006.367645