深層学習を用いた電動機の性能予測
深層学習を用いた電動機の性能予測
カテゴリ: 論文誌(論文単位)
グループ名: 【D】産業応用部門
発行日: 2022/11/01
タイトル(英語): Performance Prediction of Electric Motors via Deep Learning
著者名: 小山田 将亜(東芝三菱電機産業システム(株)長崎事業所),國松 禎明(熊本大学),水本 郁朗(熊本大学)
著者名(英語): Masatsugu Oyamada (Nagasaki Factory, Toshiba Mitsubishi-Electric Industrial Systems Co.), Sadaaki Kunimatsu (Kumamoto University), Ikuro Mizumoto (Kumamoto University)
キーワード: 深層学習,ニューラルネットワーク,電動機,性能予測,実用化_x000D_ deep learning,neural network,electric motor,performance prediction,practical use
要約(英語): When designing electric motors, many types of performances (electrical and mechanical characteristics) must be predicted with good accuracy. In general, these performances are determined based on complex theoretical calculations, but theoretical calculations include various assumptions. Therefore, it is difficult to eliminate prediction errors when predicting performance, and it is necessary to improve accuracy by referring actual test data. Recently, with the digitalization of the manufacturing process, a large amount of actual data has been converted into a database, and it is expected to be put to effective use. Here, a neural network that predicts various performances of electric motors using a large amount of actual data as a training dataset, is constructed to achieve uniform and high-precision performance prediction via deep learning. Its practical use for actual design work is verified in this study.
本誌: 電気学会論文誌D(産業応用部門誌) Vol.142 No.11 (2022)
本誌掲載ページ: 859-865 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/ieejias/142/11/142_859/_article/-char/ja/
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