Partial discharge classifications: Review of recent progress

Raymond, W.J.K. and Illias, H.A. and Abu Bakar, A.H. and Mokhlis, H. (2015) Partial discharge classifications: Review of recent progress. Measurement, 68. pp. 164-181. ISSN 0263-2241

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Abstract

It is well known that a correlation exist between the pattern of partial discharge (PD) behavior and the insulation quality. Since different sources of partial discharge have their own unique effects on the degradation of insulation material, it is vital to investigate the relationship between the defect type and the PD to determine the insulation quality. Numerous work had been done to classify partial discharge patterns with variable success. Past research work in partial discharge classification varies greatly in terms of classification techniques used, choice of feature extraction, denoising method, training process, artificial defects created for training purposes and performance assessment. Therefore it is necessary for a literature survey to access the state of the art development in partial discharge classification. (C) 2015 Elsevier Ltd. All rights reserved.

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Uncontrolled Keywords: Partial discharge measurement, pattern recognition, feature extraction, neural networks, probabilistic neural-network, pulse pattern-recognition, rough set-theory, multilayer perceptron technique, wavelet packet transform, support vector machines, hidden markov-models, fractal features, cross-wavelet, feature-extraction,
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 10 Jun 2016 00:50
Last Modified: 13 Nov 2017 08:25
URI: http://eprints.um.edu.my/id/eprint/15850

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