Wavelet Analysis for Classification of Multi-source PD Patterns

Lalitha, EM and Satish, L (2000) Wavelet Analysis for Classification of Multi-source PD Patterns. In: IEEE Transactions on Dielectrics and Electrical Insulation, 7 (1). pp. 40-47.

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Abstract

Multi-resolution signal decomposition (MSD) technique of wavelet transforms has interesting properties of capturing the embedded horizontal, vertical and diagonal variations within an image in a separable farm. This feature was exploited to identify individual partial discharge (PD) sources present in multi-source PD Patterns, usually encountered during practical PD measurements, Employing the Daubechies wavelet, features were extracted from the third level decomposed and reconstructed horizontal and vertical component images. These features were found to contain the necessary discriminating information corresponding to the individual PD sources, Suitability of these extracted features for classification was further verified using a radial basis function neural network(NN). Successful recognition was achieved, even when the constituent sources produced partially and fully overlapping patterns, thus demonstrating the applicability of the proposed novel approach for the task of multi-source PD classification.

Item Type:	Journal Article
Publication:	IEEE Transactions on Dielectrics and Electrical Insulation
Publisher:	IEEE
Additional Information:	©2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre:	Division of Electrical Sciences > High Voltage Engineering (merged with EE)
Date Deposited:	25 Aug 2008
Last Modified:	19 Sep 2010 04:15
URI:	http://eprints.iisc.ac.in/id/eprint/1795

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