ISIJ International
Online ISSN : 1347-5460
Print ISSN : 0915-1559
ISSN-L : 0915-1559
Regular Article
Computer-aided High-efficiency Detection of Fracture Initiation Sites in Steel
Miho MuramatsuZhi-Lei WangToshio OgawaYoshitaka Adachi Tetsuya NamegawaKyohei IshikawaHiroyuki ShirahataMasaaki Fujioka
著者情報
ジャーナル オープンアクセス HTML
電子付録

2022 年 62 巻 9 号 p. 1952-1956

詳細
抄録

Finding the fracture initiation sites is critical for understanding the fracture mechanism and thus improving the products’ quality, whereas some hard-to-detected features are easily missed in the human-effort-based characterizations with human eye and involve lots of labor force. In this study, computer-aided detection of fracture initiation sites is proposed to augment human expertise to efficiently find the fracture initiation sites, and thus to reduce the labor cost. With a deep-learning you only look once object detector, the fracture initiation sites of steel were successfully detected in this study. Furthermore, based on the trained detection model, an easy-to-use application for detecting initiation sites has been further developed, exhibiting great potential for high-efficiency detection of fracture initiation sites.

Fullsize Image
著者関連情報
© 2022 The Iron and Steel Institute of Japan.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs license.
https://creativecommons.org/licenses/by-nc-nd/4.0/
前の記事 次の記事
feedback
Top