Title :
Fault diagnosis of power transformers: application of fuzzy set theory, expert systems and artificial neural networks
Author :
Xu, W. ; Wang, D. ; Zhou, Z. ; Chen, H.
Author_Institution :
Dept. of Electr. Eng., Southeast Univ., Nanjing, China
fDate :
1/1/1997 12:00:00 AM
Abstract :
The application of fuzzy set theory, expert systems and artificial neural networks to fault diagnosis of power transformers is introduced, and uncertain reasoning and the combination between ES and ANN are studied. Uncertain reasoning is the main diagnostic method. The ES/ANN combination, called the consultative mechanism, can help to improve the correctness of the diagnosis and ensure the accuracy of the knowledge base. Experimental results are given which verify the proposed method
Keywords :
backpropagation; diagnostic expert systems; fault diagnosis; fuzzy set theory; knowledge acquisition; neural nets; power system analysis computing; power transformers; uncertainty handling; artificial neural networks; characteristic gas method; consultative mechanism; dissolved-gas analysis; expert systems; fault diagnosis; fuzzy set theory; knowledge base accuracy; power transformers; reasoning engine; uncertain reasoning;
Journal_Title :
Science, Measurement and Technology, IEE Proceedings -
DOI :
10.1049/ip-smt:19970856
