Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

This paper proposes a method for the reliable fault detection and classification of induction motors using two-dimensional (2D) texture features and a multiclass support vector machine (MCSVM). The proposed model first converts time-domain vibration signals to 2D gray images, resulting in texture pa...

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Bibliographic Details
Main Authors:	Jia Uddin, Myeongsu Kang, Dinh V. Nguyen, Jong-Myon Kim
Format:	Article
Language:	English
Published:	Hindawi Limited 2014-01-01
Series:	Mathematical Problems in Engineering
Online Access:	http://dx.doi.org/10.1155/2014/814593

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