Utilization of Deep Learning for The Improvement of Design Efficiency in The Field of Electric Machinery

Shinji WAKAO

doi:10.14243/jsaem.30.390

特集「AIによる電気機器の設計・解析技術」

電気機器分野における設計効率化に向けた深層学習の活用

若尾真治

著者情報

キーワード: topology optimization, electric machinery, magnetic shield, auto-encoder, response surface approximation, convolutional neural network, latent variables, deep image prior

ジャーナルフリー

2022 年 30 巻 4 号 p. 390-393

DOI https://doi.org/10.14243/jsaem.30.390

詳細

抄録

　Recently, many studies using deep learning have been reported in the field of design optimization of electric machinery based on electromagnetic field analysis. It is expected to bring unprecedented sophistication to design technology by performing complementary combination of the deductive finite element analysis with an inductive approach that constructs a Blackbox model between input and output through learning based on a large amount of data. This paper introduces some examples of effective use of both in the field of electric equipment design.

責任著者(Corresponding author)

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