DocumentCode :
2510874
Title :
ARM based induction motor fault detection using wavelet and support vector machine
Author :
Jagadanand, G. ; Dias, Fedora Lia
Author_Institution :
Electr. & Electron., Nat. Inst. of Technol., Calicut, India
fYear :
2015
fDate :
19-21 Feb. 2015
Firstpage :
1
Lastpage :
4
Abstract :
This paper proposes a Motor Current Signature Analysis technique to diagnose the stator inter turn fault in induction motor using wavelet transform and Support Vector Machine as tools. This technique is based on the analysis of stator current under both healthy and faulty conditions. Lifting algorithm based wavelet decomposition is implemented in ARM processor based system using which the approximation and detail coefficients of the three phase induction motor stator current signal are obtained. Standard deviation of these wavelet coefficients is identified as the exact feature for stator inter turn fault and fed to SVM which is then used to classify the fault. The whole system for condition monitoring is realized in ARM processor based board to reduce the implementation cost.
Keywords :
condition monitoring; fault diagnosis; induction motors; power engineering computing; reduced instruction set computing; support vector machines; wavelet transforms; ARM processor-based system; ARM-based induction motor fault detection; SVM; condition monitoring; fault classification; faulty condition; healthy condition; lifting algorithm-based wavelet decomposition; motor current signature analysis technique; stator current; stator inter turn fault diagnosis; support vector machine; three-phase induction motor stator current signal; wavelet coefficient standard deviation; wavelet transform; Induction motors; Standards; Stator windings; Support vector machines; Wavelet transforms; ARM Processor; Induction motor; Motor current signature analysis (MCSA); Support vector machine (SVM); Wavelet analysis; fault detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015 IEEE International Conference on
Conference_Location :
Kozhikode
Type :
conf
DOI :
10.1109/SPICES.2015.7091503
Filename :
7091503
Link To Document :
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