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Time-frequency based pattern recognition technique for detection and classification of power quality disturbances

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3 Author(s)
Chilukuri, M.V. ; Multimedia Univ., Cyberjaya, Malaysia ; Dash, P.K. ; Basu, K.P.

This paper proposes a simple time-frequency based pattern recognition technique for detection, classification and quantification of power quality disturbance waveforms. The proposed technique consists of time-frequency analysis, feature extraction, and pattern classification. Though there are several time-frequency analysis techniques exists in the literature, this paper uses S-transform to obtain the time-frequency characteristics of power quality events because of its superior performance under noise as well as harmonics. Using the time-frequency characteristics, a set of optimal features are extracted for pattern classification of power quality disturbances. Finally, a simple rule based system is developed for detection and classification of various power quality disturbances. Although the authors have proposed recently an S-transform based fuzzy expert system for power quality detection and classification, the proposed technique is simple and 98% accurate even under the presence of harmonics and high signal to noise ratio for the most of power quality disturbances.

Published in:

TENCON 2004. 2004 IEEE Region 10 Conference  (Volume:C )

Date of Conference:

21-24 Nov. 2004

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