機械学習を用いた電界算出に向けた基礎検討

カテゴリ: 論文誌(論文単位)

グループ名: 【B】電力・エネルギー部門

発行日: 2018/04/01

タイトル(英語): Basic Study for Electric Field Calculation by Application of Machine Learning

著者名: 加藤　克巳（新居浜工業高等専門学校），加藤　茂（新居浜工業高等専門学校），松友　真哉（新居浜工業高等専門学校）

著者名(英語): Katsumi Kato (National Institute of Technology, Niihama College), Shigeru Kato (National Institute of Technology, Niihama College), Shinya Matsutomo (National Institute of Technology, Niihama College)

キーワード: 電界解析，絶縁設計，機械学習，ニューラルネットワーク，人工知能　　electric field analysis，insulation design，machine learning，neural networks，artificial intelligence

要約(英語): Electric field analysis is one of the most important tools for the insulation design of high voltage power apparatus. The efficient method of electric field analysis is required for the insulation design and its optimization processes. In this paper, we made basic study for a process on electric field calculation with the aid of a machine learning technique. A lot of data by electric field analysis are used for the machine learning process. The machine learning is carried out before the analyzed configuration are determined. As a result, it is expected to obtain the electric field analysis results with less calculation time. As a first step, the basic availability of the process is confirmed by using the calculation examples.

本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.138 No.4 （2018）

本誌掲載ページ: 297-302 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejpes/138/4/138_297/_article/-char/ja/