On the use of stationary wavelet packet transform and multiclass wavelet SVM for broken rotor bar detection

This paper proposes an original combination of Stationary Wavelet Packet Transform (SWPT) and Multiclass Wavelet Support Vector Machines (MWSVM) to detect broken rotor bar (BRB) in induction motor (IM). The SWPT is used for feature extraction under lower sampling rate. MWSVM is developed to perform...

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Bibliographic Details
Main Authors: Keskes, H., Braham, A., Lachiri, Z.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Amplitude modulation
broken-rotorbar
Discrete wavelet transforms
Fault detection
Harmonic analysis
induction motors
pattern recognition
support vector machines
wavelet transforms
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Summary:This paper proposes an original combination of Stationary Wavelet Packet Transform (SWPT) and Multiclass Wavelet Support Vector Machines (MWSVM) to detect broken rotor bar (BRB) in induction motor (IM). The SWPT is used for feature extraction under lower sampling rate. MWSVM is developed to perform the faults recognition. Different binary Multiclass SVM strategies are compared with various wavelet kernel functions in terms of classification accuracy, training and testing complexity. The experimental results show that the proposed method is able to detect the faulty conditions with high accuracy.
ISSN:1553-572X
DOI:10.1109/IECON.2012.6389266