By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

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