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

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	110-116
Number of pages	7
Journal	Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Volume	112
Issue number	2
Publication status	Published - 1992

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

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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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TY - JOUR

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

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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

Abstract

ASJC Scopus subject areas

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