DocumentCode :
2300652
Title :
Research on transformer fault diagnosis based on genetic algorithm of ENN
Author :
Gong Ruikun ; Lu Fuqiang ; Wang Xinze
Author_Institution :
Coll. of Electr. Eng., HeBei United Univ. Tangshan, Tangshan, China
fYear :
2012
fDate :
29-31 Dec. 2012
Firstpage :
834
Lastpage :
837
Abstract :
For the characteristics of transformer fault diagnosis, this paper puts forward a method based on genetic algorithm and extension neural network power transformer fault diagnosis methods. This paper introduces the double right extension neural network structure; and structure based on genetic algorithm and extension neural network fault diagnosis model and algorithm design, and its application to the diagnosis of power transformer identification; Through the simulation experiment shows the method is simple, training error is small, fast convergence time etc.
Keywords :
fault diagnosis; genetic algorithms; neural nets; power engineering computing; power transformers; ENN; extension neural network power transformer fault diagnosis method; genetic algorithm; power transformer identification; right extension neural network structure; extension neural network; genetic algorithm; transformer fault diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
Type :
conf
DOI :
10.1109/ICCSNT.2012.6526059
Filename :
6526059
Link To Document :
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