Please use this identifier to cite or link to this item:
Title: An integrated data compression scheme for power quality events using spline wavelet and neural network
Authors: Meher, S K
Pradhan, A K
Panda, G
Keywords: Power quality
Data compression wavelet transform
Spline wavelet
Neural network
Issue Date: 2004
Publisher: Elsevier
Citation: Electric Power Systems Research, Vol 69, Iss 2-3, P 213-220
Abstract: Spline wavelet (SW) is an optimum wavelet among the various existing wavelets which possesses some superior properties like regularity, best approximation and compactness at a given order over other conventional bases. In this paper a novel integrated approach for power quality data compression using the SW transform (SWT) and neural network is presented and its performance is assessed in terms of compression ratio (CR), mean square error and percentage of energy retained in the reconstructed signals. 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. Computer simulation results indicate that the proposed scheme offers superior compression performance compared to the conventional discrete cosine transform (DCT) and the discrete wavelet transform (DWT)-based approaches.
Description: Copyright for this article belongs to Elsevier Science Ltd
Appears in Collections:Journal Articles

Files in This Item:
File Description SizeFormat 
pandag1.pdf312.47 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.