Journal ArticleDOI
Determination of neural-network topology for partial discharge pulse pattern recognition
Magdy M. A. Salama,Ray Bartnikas +1 more
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TLDR
The cascaded output neural-network structure was found to provide the highest success rate in differentiating between two different partial discharge patterns by utilizing the indexed feature of the first stage output as one of the inputs into the second stage of the cascaded neural network.Abstract:
A time-series approach has been employed to devise neural-network topologies for time dependent partial discharge pulse pattern recognition applications. The cascaded output neural-network structure was found to provide the highest success rate in differentiating between two different partial discharge patterns. This was accomplished by utilizing the indexed feature of the first stage output as one of the inputs into the second stage of the cascaded neural network.read more
Citations
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Journal ArticleDOI
Partial discharges. Their mechanism, detection and measurement
TL;DR: Different partial discharge detection and measurement procedures suitable for use on cables, capacitors, transformers and rotating machines are examined and compared in this paper, with particular attention given in regard to their suitability to different types of electrical apparatus and cable specimens under test as well as their applicability to discharge site location and their capability to detect different forms of PD.
Journal ArticleDOI
Partial discharge diagnostics and electrical equipment insulation condition assessment
TL;DR: Partial discharge (PD) measurement has been widely applied to diagnose the condition of the electrical insulation in operating apparatus such as switchgear, transformers, cables, as well as motor and generator stator windings.
Journal ArticleDOI
Trends in partial discharge pattern classification: a survey
TL;DR: Partial discharge detection, measurement, and classification constitute an important tool for quality assessment of insulation systems utilized in HV power apparatus and cables as mentioned in this paper, and various techniques available for achieving the foregoing task are examined and analyzed; while limited success has been achieved in the identification of simple PD sources, recognition and classification of complex PD patterns associated with practical insulating systems still pose appreciable difficulty.
Journal ArticleDOI
Partial discharge classifications: Review of recent progress
TL;DR: In this paper, the authors present a literature survey to access the state-of-the-art development in partial discharge classification, which 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.
Journal ArticleDOI
Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network
D. Evagorou,Andreas Kyprianou,Paul Lewin,Andreas Stavrou,Venizelos Efthymiou,A C Metaxas,George E. Georghiou +6 more
TL;DR: In this paper, the moments of the probability density function (PDF) of the wavelet coefficients at various scales, obtained through wavelet packets transformation, were used as a fingerprint for partial discharge (PD) classification.
References
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Book
Time series modelling of water resources and environmental systems
Keith W. Hipel,T. I. McLeod +1 more
TL;DR: Part 1 Scope and background material: Environmetrics, Science and Decision Making, and how to deal with messy environmental data.
Journal ArticleDOI
Neural networks as a tool for recognition of partial discharges
E. Gulski,A. Krivda +1 more
TL;DR: In this article, three different neural networks (NNs) were applied to the recognition of partial discharge (PD) patterns in industrial objects, and the results of PD measurements on simple two-electrode models were presented.
Journal ArticleDOI
Automated recognition of partial discharges
TL;DR: An overview of automated recognition of partial discharges (PD) is given, and the selection of PD patterns, extraction of relevant information for PD recognition and the structure of a data base forPD recognition are discussed.
Journal ArticleDOI
Computer-aided measurement of partial discharges in HV equipment
TL;DR: In this paper, a previously developed method of partial discharge recognition is used to evaluate PD in HV devices using conventional discharge detection (bandwidth approximately 400 kHz), the PD patterns are studied.
Journal ArticleDOI
PD recognition by means of statistical and fractal parameters and a neural network
TL;DR: In this article, a novel partial discharge (PD) defect identification method is described, where a suitable set of parameters are determined and then used as input variables to a neural network for the purpose of identifying the defects within the insulation.