DocumentCode :
2298386
Title :
Fault diagnosis of induction motor rotor based on BP neural network and D-S evidence theory
Author :
Zhang, Lieping ; Wang, Shoufeng
Author_Institution :
Coll. of Inf. Sci. & Eng., Guilin Univ. of Technol., Guilin, China
fYear :
2012
fDate :
6-8 July 2012
Firstpage :
3292
Lastpage :
3297
Abstract :
Directing to the shortage of single method of BP neural network or D-S evidence theory in rotor fault diagnosis, a fault diagnostic method for induction motor rotor was proposed, which was based on BP neural network and D-S evidence theory. The BP neural network method was applied to the fault diagnosis firstly, and then, the partial diagnostic results of BP neural network were taken as the basic probability assignment, finally, the D-S evidence theory was applied to fuse different results from all the neural networks and got the finally diagnostic results. The experiment simulation results of fault diagnostic example show that the method is available for the induction motor rotor fault diagnosis and has better classified diagnosis ability than single fault diagnostic method.
Keywords :
backpropagation; electric machine analysis computing; fault diagnosis; induction motors; neural nets; rotors; BP neural network method; D-S evidence theory; basic probability assignment; fault diagnostic method; induction motor rotor; single method; Educational institutions; Fault diagnosis; Induction motors; Intelligent control; Manganese; Neural networks; Rotors; BP neural network; D-S evidence theory; induction motor; rotor fault diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
Type :
conf
DOI :
10.1109/WCICA.2012.6358441
Filename :
6358441
Link To Document :
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