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Comparison of BP and SOM as a Classification of PD Source

부분방전원의 분류에 있어서 BP와 SOM의 비교

  • 박성희 (충북대학교 전기전자컴퓨터공학부) ;
  • 강성화 (충청대학 산업안전과) ;
  • 임기조 (충북대학교 전기전자컴퓨터공학부)
  • Published : 2004.09.01

Abstract

In this paper, neural networks is studied to apply as a PD source classification in XLPE power cable specimen. Two learning schemes are used to classification; BP(Back propagation algorithm), SOM(self organized map - kohonen network). As a PD source, using treeing discharge sources in the specimen, three defected models are made. 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 a]so these distribution characteristics are applied to classify PD sources by two scheme of the neural networks. In conclusion, recognition efficiency of BP is superior to SOM.

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