NDLI: Recursive Undecimated Wavelet Packet Transform and DAG SVM for Induction Motor Diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Keskes, H. Braham, A.
Copyright Year	2005
Abstract	This paper is focused on the design of a new approach dedicated to solve classification problems for the detection of broken rotor bar (BRB) fault in induction motors (IM). This new method finds its origins in a novel combination of both recursive undecimated wavelet packet transform (RUWPT) and directed acyclic graph support vector machines (DAG SVMs). Most often, BRB frequency components are hardly detected in the stator current due to its low magnitude and closeness to the supply frequency component. To overcome this drawback, the RUWPT is applied to extract one parameter able to detect the fault with arbitrary working conditions and a great concern of low load cases. Different multiclass support vector machines (MSVMs) methods are evaluated with respect to accuracy, number of support vectors, and testing time. The experimental results confirm that the DAG SVMs and Symlet wavelet kernel function are fast, robust, and give the best classification accuracy of 99%.
Sponsorship	IEEE Industrial Electronics Society
Starting Page	1059
Ending Page	1066
Page Count	8
File Size	1364015
File Format	PDF
ISSN	15513203
Volume Number	11
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Kernel Induction motors Feature extraction Discrete wavelet transforms Support Vector Machines Fault detection Induction Motor Broken- Rotor-Bar Wavelet Transforms Pattern Recognition wavelet transforms Broken rotor bar (BRB) fault detection induction motor (IM) pattern recognition support vector machines (SVMs)
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Information Systems Electrical and Electronic Engineering Computer Science Applications

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