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Detection and Classification of Power Quality Disturbancewaveform Using MRA Based Modified Wavelet Transfrom and Neural Networks Cover

Detection and Classification of Power Quality Disturbancewaveform Using MRA Based Modified Wavelet Transfrom and Neural Networks

Open Access
|Jun 2011

Abstract

In this paper, the modified wavelet based artificial neural network (ANN) is implemented and tested for power signal disturbances. The power signal is decomposed by using modified wavelet transform and the classification is carried by using ANN. Discrete modified wavelet transforms based signal decomposition technique is integrated with the back propagation artificial neural network model is proposed. Varieties of power quality events including voltage sag, swell, momentary interruption, harmonics, transient oscillation and voltage fluctuation are used to test the performance of the proposed approach. The simulation is carried out by using MATLAB software. The simulation results show that the proposed scheme offers superior detection and classification compared to the conventional approaches.

DOI: https://doi.org/10.2478/v10187-010-0033-4 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
Language: English
Page range: 235 - 240
Published on: Jun 7, 2011
Published by: Slovak University of Technology in Bratislava
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2011 Perumal Chandrasekar, Vijayarajan Kamaraj, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons License.

Volume 61 (2010): Issue 4 (July 2010)