NDLI: Research on fault diagnosis method of high-voltage circuit breaker based on fuzzy neural network data fusion

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Research on fault diagnosis method of high-voltage circuit breaker based on fuzzy neural network data fusion

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Research on fault diagnosis method of high-voltage circuit breaker based on fuzzy neural network data fusion

Content Provider	IEEE Xplore Digital Library
Author	Miao Hongxia Wang Honghua
Copyright Year	2010
Description	Author affiliation: Key laboratory of power transmission, distribution and power saving technology, Changzhou China (Miao Hongxia) \|\| College of Electrical, Hohai University, Nanjing China (Wang Honghua)
Abstract	High-voltage circuit breakers are important electrical equipments which play the role of protection and control in the power network. In order to make the power system operate in a stable and reliable way, it is of great significance to make online fault diagnosis. This paper introduced the method of feature level data fusion using fuzzy neural network, and applied it into the fault diagnosis of high-voltage breakers. The results of the diagnosis showed that the model had good fault identification capability, it could deal very well with both the uncertain knowledge and ambiguous data, as well as improve the accuracy of fault diagnosis.
File Size	867234
File Format	PDF
ISBN	9781424472352
e-ISBN	9781424472376
DOI	10.1109/ICCASM.2010.5623219
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Training High-voltage circuit breaker Circuit breakers Artificial neural networks Fuzzy neural networks Data fusion Fuzzy neural network Circuit faults Biological neural networks
Content Type	Text
Resource Type	Article

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