Recognition of partial discharge pattern of electrode voids by neural network

Takashi Yanagisawa; Shinichi Iwamoto; Tatsuki Okamoto; Hiromasa Fukagawa

Recognition of partial discharge pattern of electrode voids by neural network

Takashi Yanagisawa^*, Shinichi Iwamoto, Tatsuki Okamoto, Hiromasa Fukagawa

^*この研究の対応する著者

研究成果: Article › 査読

抄録

A back-propagation neural network model is used to identify electrode types involved in partial discharge (tree, IEC (b), CIGRE method I) and to estimate the shapes of the cylindrical electrode voids, based on the specific charge-phase characteristics of the different electrode types.

本文言語	English
ページ（範囲）	110-116
ページ数	7
ジャーナル	Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
巻	112
号	2
出版ステータス	Published - 1992

ASJC Scopus subject areas

電子工学および電気工学

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title = "Recognition of partial discharge pattern of electrode voids by neural network",

abstract = "A back-propagation neural network model is used to identify electrode types involved in partial discharge (tree, IEC (b), CIGRE method I) and to estimate the shapes of the cylindrical electrode voids, based on the specific charge-phase characteristics of the different electrode types.",

author = "Takashi Yanagisawa and Shinichi Iwamoto and Tatsuki Okamoto and Hiromasa Fukagawa",

year = "1992",

language = "English",

volume = "112",

pages = "110--116",

journal = "Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)",

issn = "0424-7760",

publisher = "John Wiley and Sons Inc.",

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T1 - Recognition of partial discharge pattern of electrode voids by neural network

AU - Yanagisawa, Takashi

AU - Iwamoto, Shinichi

AU - Okamoto, Tatsuki

AU - Fukagawa, Hiromasa

PY - 1992

Y1 - 1992

N2 - A back-propagation neural network model is used to identify electrode types involved in partial discharge (tree, IEC (b), CIGRE method I) and to estimate the shapes of the cylindrical electrode voids, based on the specific charge-phase characteristics of the different electrode types.

AB - A back-propagation neural network model is used to identify electrode types involved in partial discharge (tree, IEC (b), CIGRE method I) and to estimate the shapes of the cylindrical electrode voids, based on the specific charge-phase characteristics of the different electrode types.

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M3 - Article

AN - SCOPUS:0026706011

SN - 0424-7760

VL - 112

SP - 110

EP - 116

JO - Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)

JF - Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)

IS - 2

ER -

Recognition of partial discharge pattern of electrode voids by neural network

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ASJC Scopus subject areas

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