DocumentCode :
2232002
Title :
Motor current signature analysis by multi-resolution methods using Support Vector Machine
Author :
Moorthy, Yamuna K. ; Chandran, Pournami S. ; Rishidas, S.
Author_Institution :
Dept. of Electron. & Commun., Coll. of Eng., Trivandrum, Trivandrum, India
fYear :
2011
fDate :
22-24 Sept. 2011
Lastpage :
101
Abstract :
This paper presents a method for induction motor fault diagnosis based on rotor current signal analysis using Support Vector Machine. A dynamic model of induction motor developed using SIMULINK/MATLAB environment is used for simulation testing. A rotor fault is incorporated into the developed dynamic model which is mathematically complaint. The simulated model gives rotor currents, the multi-resolution analysis of which is conducted in the wavelet domain for the detection of broken bars. The analyzed data itself is indicative of the incipient faults, but mere human inspection can sometimes lead to unexpected faults. Hence, a classification scheme using Support Vector Machine is adopted. Finally, the results of Support Vector classification is compared against that of Artificial Neural Networks.
Keywords :
digital simulation; electric machine analysis computing; fault diagnosis; induction motors; support vector machines; wavelet transforms; SIMULINK-MATLAB environment; broken bar detection; induction motor fault diagnosis; motor current signature analysis; multiresolution method; rotor current signal analysis; support vector classification; support vector machine; wavelet domain; Discrete cosine transforms; Equations; Induction motors; Integrated circuit modeling; Mathematical model; Rotors; Support vector machines; Fault detection; Support Vector Machine; broken rotor bars; modeling; wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Advances in Intelligent Computational Systems (RAICS), 2011 IEEE
Conference_Location :
Trivandrum
Print_ISBN :
978-1-4244-9478-1
Type :
conf
DOI :
10.1109/RAICS.2011.6069280
Filename :
6069280
Link To Document :
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