Bearing fault detection of induction motor using wavelet and Support Vector Machines (SVMs)

Condition monitoring of induction motors is a fast emerging technology in the field of electrical equipment maintenance and has attracted more and more attention worldwide as the number of unexpected failure of a critical system can be avoided. Keeping this in mind a bearing fault detection scheme of three-phase inductionmotor has been attempted. In the present study, Support VectorMachine (SVM) is used alongwith continuouswavelet transform (CWT), an advanced signal-processing tool, to analyze the frame vibrations during start-up. CWT has not been widely applied in the field of condition monitoring eywords: ondition monitoring nduction motor earing fault ontinuous wavelet transform (CWT) althoughmuch better results can been obtained compared to thewidely usedDWTbased techniques. The encouraging results obtained from the present analysis is hoped to set up a base for condition monitoring technique of induction motor which will be simple, fast and overcome the limitations of traditional data-based models/techniques. © 2011 Elsevier B.V. All rights reserved. upport Vector Machine (SVM)