- 부분방전원의 분류에 있어서 BP와 SOM의 비교
- ㆍ 저자명
- 박성희,강성화,임기조
- ㆍ 간행물명
- 전기전자재료학회논문지
- ㆍ 권/호정보
- 2004년|17권 9호|pp.1006-1012 (7 pages)
- ㆍ 발행정보
- 한국전기전자재료학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
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.