• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.10
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• pp.879-883
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• 2009

This paper was provided to help in detecting defects in power transformer. For this purpose, a partial discharge cell was designed and manufactured as a discharge source to simulate particle defected paper-oil insulation in power transformer. Experimental set-up for measuring PD signals was described. Magnitude of electromagnetic wave signals and corresponding amount of apparent discharge were measured simultaneously against phase of applied voltage to the discharge cell. Frequency range and pattern of PRPD(Phase Resolved Partial Discharge) of partial discharge signals were examined and analyzed. The results will be contributed to build the defect database of power transformer and to decrease the substation faults.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05b
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• pp.100-103
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• 2004

In this paper, BP learning algorithm is studied to apply as a PD source classification in GIS specimens. For occurred partial discharge, three defected models are made; floating particle, surface discharge of spacer, needle to plane. And PD data for discrimination were acquired from PD detector. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.