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http://dx.doi.org/10.9708/jksci.2011.16.3.141

Fault Detection and Diagnosis of Induction Motors using LPC and DTW Methods  

Hwang, Chul-Hee (School of Electrical Engineering, University of Ulsan)
Kim, Yong-Min (School of Electrical Engineering, University of Ulsan)
Kim, Cheol-Hong (Dept. of Electronics and Computer Eng., Chonnam National University)
Kim, Jong-Myon (School of Electrical Engineering, University of Ulsan)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.3, 2011 , pp. 141-147 More about this Journal
Abstract
This paper proposes an efficient two-stage fault prediction algorithm for fault detection and diagnosis of induction motors. In the first phase, we use a linear predictive coding (LPC) method to extract fault patterns. In the second phase, we use a dynamic time warping (DTW) method to match fault patterns. Experiment results using eight vibration data, which were collected from an induction motor of normal fault states with sampling frequency of 8 kHz and sampling time of 2.2 second, showed that our proposed fault prediction algorithm provides about 45% better accuracy than a conventional fault diagnosis algorithm. In addition, we implemented and tested the proposed fault prediction algorithm on a testbed system including TI's TMS320F2812 DSP that we developed.
Keywords
fault detection and diagnosis; linear predictive coding; dynamic time warping; induction motor;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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