Imagery creation based on autonomic system for finite element by using fully convolutional network

Gentaro Miyaki, Komei Tanaka, Hiroshi Hasegawa

研究成果: Conference article

抄録

For applications in Industry 4.0, a system that can analyze the deformation and stress of a target object from an image acquired by a smartphone or tablet is proposed in this paper. The process for the proposed system is more convenient for users than creating a computer-aided design model. The target objects include bridges and plant equipment, and the proposed process aims to facilitate maintenance inspections. To acquire results from this system, a fully convolutional network is employed to extract the target object from the obtained image, and density-based topology optimization is applied to produce a finite element model, which is imported to commercial software. Artificial intelligence image processing is adopted to generate the output of the finite element model for the target object. In this work, numerical examples demonstrate that the final model for the target object is accurate and appropriate for finite element deformation and stress analysis.

本文言語English
ページ(範囲)383-386
ページ数4
ジャーナルProcedia Manufacturing
42
DOI
出版ステータスPublished - 2020
イベント1st International Conference on Industry 4.0 and Smart Manufacturing, ISM 2019 - Rende (CS), Italy
継続期間: 2019 11 202019 11 22

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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