DocumentCode :
2306929
Title :
Fault Diagnosis Algorithm Based on Artificial Immunity System
Author :
Aydin, Ilhan ; Karakose, Mehmet ; Akin, Erhan
Author_Institution :
Firat Univ., Elazig
fYear :
2006
fDate :
17-19 April 2006
Firstpage :
1
Lastpage :
4
Abstract :
Artificial immunity systems have been emerged as simulation of human immunity. The negative selection algorithm which is most important component of artificial immunity system can determine undesired condition, easily. In this study, motor current signature analysis and negative selection algorithm have been used for broken rotor bar faults. Current signal obtained from motor has been transformed to current spectrum by using motor current signature analysis. The side bands extracted from this spectrum have been taken as input to negative selection algorithm, and broken rotor bar faults have been diagnosed. The application of developed fault diagnosis algorithm has been demonstrated by diagnosing faults in induction motor real time. Furthermore, proposed fault diagnosis approach is adapted for diagnosing other faults
Keywords :
fault location; induction motors; rotors; signal processing; artificial immunity system; broken rotor bar fault; current signature analysis; current spectrum; fault diagnosis algorithm; induction motor; negative selection algorithm; side band extraction; Algorithm design and analysis; Fault diagnosis; Humans; Immune system; Induction motors; Rotors; Stators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications, 2006 IEEE 14th
Conference_Location :
Antalya
Print_ISBN :
1-4244-0238-7
Type :
conf
DOI :
10.1109/SIU.2006.1659876
Filename :
1659876
Link To Document :
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