Title :
Neural networks based on fuzzy clustering and its applications in electrical equipment´s fault diagnosis
Author_Institution :
Dept. of Electr. & Inf. Eng., Wuhan Polytech. Univ., China
Abstract :
This article put forward a sample processing method using fuzzy clustering and studied the application of fuzzy competition classification method in extracting contradiction samples, then advanced the diagnosis method of neural network based on fuzzy clustering, finally carried on the simulation research. The calculation results show that all the above-mentioned methods are quite practical.
Keywords :
electrical engineering computing; electrical faults; fault diagnosis; feature extraction; fuzzy neural nets; fuzzy set theory; pattern classification; pattern clustering; signal classification; signal sampling; contradiction sample extraction; electrical equipment fault diagnosis; fuzzy clustering; fuzzy competition classification; neural networks; sample processing; Electronic equipment; Electronic mail; Fault diagnosis; Fuzzy neural networks; Fuzzy set theory; Fuzzy systems; Intelligent networks; Neural networks; Oil insulation; Shape; Neural network; electrical equipment; fault diagnosis; fuzzy clustering;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527636
