DocumentCode
581361
Title
On the use of stationary wavelet packet transform and multiclass wavelet SVM for broken rotor bar detection
Author
Keskes, Hassen ; Braham, Ahmed ; Lachiri, Zied
Author_Institution
Res. Lab., INSAT, Tunisia
fYear
2012
fDate
25-28 Oct. 2012
Firstpage
3919
Lastpage
3924
Abstract
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.
Keywords
electric machine analysis computing; fault diagnosis; feature extraction; induction motors; rotors; support vector machines; wavelet transforms; IM; MWSVM; SWPT; binary multiclass SVM strategies; broken rotor bar detection; classification accuracy; faults recognition; feature extraction; induction motor; multiclass wavelet support vector machines; sampling rate; stationary wavelet packet transform; testing complexity; training; Accuracy; Amplitude modulation; Discrete wavelet transforms; Harmonic analysis; Fault detection; broken-rotorbar; induction motors; pattern recognition; support vector machines; wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
Conference_Location
Montreal, QC
ISSN
1553-572X
Print_ISBN
978-1-4673-2419-9
Electronic_ISBN
1553-572X
Type
conf
DOI
10.1109/IECON.2012.6389266
Filename
6389266
Link To Document