DocumentCode :
2544261
Title :
Fuzzy fault diagnosis method based on particle swarm optimization algorithm
Author :
Wang, Yonglin ; Wen, Shengjun ; Wang, Dongyun
Author_Institution :
Sch. of Electron. Inf., Zhongyuan Univ. of Technol., Zhengzhou, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
307
Lastpage :
310
Abstract :
A new fuzzy fault diagnosis method using particle swarm optimization (PSO) algorithm to determine its membership function is proposed in view of weights training technology of neural network. The brief introduction to fuzzy fault diagnosis method based on fuzzy classification concept is described at first. Then the process of obtaining membership function using PSO algorithm is demonstrated. A fitness function for fault diagnosis is presented. Finally, a numerical simulation for fault diagnosis of steam turbine-generator sets is given to verify the effectiveness of the proposed method.
Keywords :
boilers; fault diagnosis; fuzzy set theory; neural nets; particle swarm optimisation; power engineering computing; steam turbines; PSO; fuzzy classification concept; fuzzy fault diagnosis method; membership function; neural network; numerical simulation; particle swarm optimization algorithm; steam turbine-generator; weights training technology; Educational institutions; Fault diagnosis; Generators; Indexes; Particle swarm optimization; Testing; Training; PSO algorithm; fuzzy fault diagnosis; membership function; turbine-generator sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
Type :
conf
DOI :
10.1109/FSKD.2012.6233896
Filename :
6233896
Link To Document :
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