Wavelet packet decomposition-based fault diagnosis scheme for SRM drives with a single current sensor

Gan, Chun, Wu, Jianhua, Yang, Shiyou, Hu, Yihua and Cao, Wenping (2016). Wavelet packet decomposition-based fault diagnosis scheme for SRM drives with a single current sensor. IEEE Transactions on Energy Conversion, 31 (1), pp. 303-313.

Abstract

Power converters are a key, but vulnerable component in switched reluctance motor (SRM) drives. In this paper, a new fault diagnosis scheme for SRM converters is proposed based on the wavelet packet decomposition (WPD) with a dc-link current sensor. Open- and short-circuit faults of the power switches in an asymmetrical half-bridge converter are analyzed in details. In order to obtain the fault signature from the phase currents, two pulse-width modulation signals with phase shift are injected into the lower-switches of the converter to extract the excitation current, and the WPD algorithm is then applied to the detected currents for fault diagnosis. Moreover, a discrete degree of the wavelet packet node energy is chosen as the fault coefficient. The converter faults can be diagnosed and located directly by determining the changes in the discrete degree from the detected currents. The proposed scheme requires only one current sensor in the dc link, while conventional methods need one sensor for each phase or additional detection circuits. The experimental results on a 750-W three-phase SRM are presented to confirm the effectiveness of the proposed fault diagnosis scheme.

Publication DOI: https://doi.org/10.1109/TEC.2015.2476835
Divisions: Engineering & Applied Sciences
Additional Information: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Full Text Link: http://ieeexplo ... rnumber=7307160
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Published Date: 2016-03
Authors: Gan, Chun
Wu, Jianhua
Yang, Shiyou
Hu, Yihua
Cao, Wenping ( 0000-0002-8133-3020)

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Version: Accepted Version


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