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http://dx.doi.org/10.5370/JEET.2015.10.4.1558

Support Vector Machine Based Bearing Fault Diagnosis for Induction Motors Using Vibration Signals  

Hwang, Don-Ha (HVDC Research Division, Korea Electrotechnology Research Institute (KERI))
Youn, Young-Woo (HVDC Research Division, Korea Electrotechnology Research Institute (KERI))
Sun, Jong-Ho (HVDC Research Division, Korea Electrotechnology Research Institute (KERI))
Choi, Kyeong-Ho (Dept. of Railroad Electricity, Kyungbuk College)
Lee, Jong-Ho (Dept. of Electronic Engineering, Gachon University)
Kim, Yong-Hwa (Dept. of Electronic Engineering, Yongin, Myongji University)
Publication Information
Journal of Electrical Engineering and Technology / v.10, no.4, 2015 , pp. 1558-1565 More about this Journal
Abstract
In this paper, we propose a new method for detecting bearing faults using vibration signals. The proposed method is based on support vector machines (SVMs), which treat the harmonics of fault-related frequencies from vibration signals as fault indices. Using SVMs, the cross-validations are used for a training process, and a two-stage classification process is used for detecting bearing faults and their status. The proposed approach is applied to outer-race bearing fault detection in three-phase squirrel-cage induction motors. The experimental results show that the proposed method can effectively identify the bearing faults and their status, hence improving the accuracy of fault diagnosis.
Keywords
Bearing fault; Induction motor; Fault diagnosis; Vibration signal;
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