NDLI: Motor current signature analysis by multi-resolution methods using Support Vector Machine

Content Provider	IEEE Xplore Digital Library
Author	Moorthy, Y.K. Chandran, P.S. Rishidas, S.
Copyright Year	2011
Description	Author affiliation: Dept of Electronics & Communication, College of Engineering Trivandrum, 695016, India (Chandran, P.S.) \|\| Dept of Electronics & Communication, College of Engineering, Trivandrum, 695016, India (Moorthy, Y.K.; Rishidas, S.)
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.
Starting Page	096
Ending Page	101
File Size	730707
Page Count	6
File Format	PDF
ISBN	9781424494781
e-ISBN	9781424494774
DOI	10.1109/RAICS.2011.6069280
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Induction motors Fault detection Rotors Broken rotor bars Wavelet analysis Support Vector Machine Mathematical model Discrete cosine transforms Integrated circuit modeling Modeling Equations
Content Type	Text
Resource Type	Article

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