[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.4313/JKEM.2004.17.9.1006

Comparison of BP and SOM as a Classification of PD Source

박성희 (충북대학교 전기전자컴퓨터공학부)
강성화 (충청대학 산업안전과)
임기조 (충북대학교 전기전자컴퓨터공학부)

Publication Information

Journal of the Korean Institute of Electrical and Electronic Material Engineers / v.17, no.9, 2004 , pp. 1006-1012 More about this Journal

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.

Keywords

PD; Solid Insulator; Statistical Distribution; BP; SOM;

Citations & Related Records

Times Cited By KSCI : 2 (Citation Analysis)

Reference
Cited By KSCI

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KSCI

Comparison of BP and SOM as a Classification of PD Source 부분방전원의 분류에 있어서 BP와 SOM의 비교

Comparison of BP and SOM as a Classification of PD Source