DocumentCode :
2456262
Title :
An application of genetic algorithm and fuzzy logic for the induction motor diagnosis
Author :
Razik, H. ; Corrêa, M. B R ; Silva, E. R C da
Author_Institution :
GREEN-UHP - UMR-7037, Univ. Henri Poincare - Nancy 1, Vandoeuvre-les-Nancy
fYear :
2008
fDate :
10-13 Nov. 2008
Firstpage :
3067
Lastpage :
3072
Abstract :
The aim of this paper is the diagnosis of signatures of rotor broken bars when the induction machine is fed by an unbalanced line voltage. These signatures are given by the complex spectrum modulus of the line current. In order to make the diagnostic, a genetic algorithm is used to keep the amplitude of all faulty lines. Moreover, the fuzzy logic approach allows us to conclude to the load level operating system as to inform the operator of the rotor fault severity. Experimental results proof the performance of this method under various load levels and various fault severities. The conclusion resulting from this study is highlighted and proves the efficiency of the suggested approach.
Keywords :
fault diagnosis; fuzzy logic; genetic algorithms; induction motors; complex spectrum modulus; fuzzy logic; genetic algorithm; induction machine; induction motor diagnosis; line current; rotor broken bars; rotor fault; unbalanced line voltage; Fault detection; Frequency; Fuzzy logic; Genetic algorithms; Induction machines; Induction motors; Monitoring; Operating systems; Rotors; Stators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2008. IECON 2008. 34th Annual Conference of IEEE
Conference_Location :
Orlando, FL
ISSN :
1553-572X
Print_ISBN :
978-1-4244-1767-4
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2008.4758450
Filename :
4758450
Link To Document :
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