DocumentCode :
2874249
Title :
Research on fault diagnosis method of high-voltage circuit breaker based on fuzzy neural network data fusion
Author :
Hongxia, Miao ; Honghua, Wang
Author_Institution :
Key Lab. of Power Transm., Distrib. & Power Saving Technol., Changzhou, China
Volume :
11
fYear :
2010
fDate :
22-24 Oct. 2010
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.
Keywords :
circuit breakers; fault diagnosis; fuzzy neural nets; power engineering computing; sensor fusion; electrical equipments; feature level data fusion; fuzzy neural network data fusion; high-voltage breakers; high-voltage circuit breakers; online fault diagnosis; power system; Artificial neural networks; Biological neural networks; Circuit breakers; Circuit faults; Fault diagnosis; Fuzzy neural networks; Training; High-voltage circuit breaker; data fusion; fault diagnosis; fuzzy neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5623219
Filename :
5623219
Link To Document :
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