DocumentCode
3564526
Title
Power transformer fault diagnosis based on chaos immune evolutionary clustering algorithm
Author
Hong-xia, Xie ; Li-ping, Shi ; Zheng-yun, Hui ; Hui, Xu
Author_Institution
China Univ. of Min. & Technol., Xuzhou, China
Volume
2
fYear
2010
Abstract
This paper researches the advantages and shortcomings of Fuzzy C-Means (FCM) algorithm which applied to transformer fault diagnosis firstly, then combine the FCM algorithm with the chaos immune evolutionary algorithm to propose a new method of transformer fault diagnosis - chaos immune evolutionary clustering algorithm. Theoretical analysis and simulation results show that the algorithm not only effectively overcome the traditional FCM clustering algorithm falling into local minimum of the shortcomings, but also effectively suppress the immune evolution process produced the "degradation" phenomenon.
Keywords
artificial immune systems; chaos; evolutionary computation; fault diagnosis; fuzzy set theory; pattern clustering; power engineering computing; power transformers; chaos immune evolutionary clustering algorithm; degradation phenomenon; fuzzy C-Means algorithm; immune evolution process; power transformer fault diagnosis; Algorithm design and analysis; Chaos; Clustering algorithms; Evolutionary computation; Fault diagnosis; Power transformers; Signal processing algorithms; Fuzzy C-Means; Immune Evolutionary; chaos optimization; fault diagnosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
Print_ISBN
978-1-4244-6892-8
Electronic_ISBN
978-1-4244-6893-5
Type
conf
DOI
10.1109/ICSPS.2010.5555714
Filename
5555714
Link To Document