DocumentCode
1506769
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
Volume
144
Issue
1
fYear
1997
fDate
1/1/1997 12:00:00 AM
Firstpage
39
Lastpage
44
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;
fLanguage
English
Journal_Title
Science, Measurement and Technology, IEE Proceedings -
Publisher
iet
ISSN
1350-2344
Type
jour
DOI
10.1049/ip-smt:19970856
Filename
575885
Link To Document