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
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