Recognition of partial discharge pattern of electrode voids by neural network

Takashi Yanagisawa, Shinichi Iwamoto, Tatsuki Okamoto, Hiromasa Fukagawa

    Research output: Contribution to journalArticle

    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 languageEnglish
    Pages (from-to)110-116
    Number of pages7
    JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
    Volume112
    Issue number2
    Publication statusPublished - 1992

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    Partial discharges
    Neural networks
    Electrodes
    Backpropagation

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

    Cite this

    Recognition of partial discharge pattern of electrode voids by neural network. / Yanagisawa, Takashi; Iwamoto, Shinichi; Okamoto, Tatsuki; Fukagawa, Hiromasa.

    In: Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi), Vol. 112, No. 2, 1992, p. 110-116.

    Research output: Contribution to journalArticle

    Yanagisawa, Takashi ; Iwamoto, Shinichi ; Okamoto, Tatsuki ; Fukagawa, Hiromasa. / Recognition of partial discharge pattern of electrode voids by neural network. In: Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi). 1992 ; Vol. 112, No. 2. pp. 110-116.
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