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 :
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