Abstract—Forging is the process of forming and shaping metals by making use of hammering or pressing. Forging is one of the main processes in metal production. Keeping quality of forged parts high is very important from the viewpoint of performance or safety of the products. Since forged part quality is checked by visual inspection whether there is any defect, it imposes a lot of loads to the workers. Although the defect detection is expected to be substituted by laser measurement or image processing instead of human eyes, comparison of both methods has hardly been carried out. In this paper, experimental results to detect defects by both methods are described for one forged part. Especially, comparison between frequency analysis by Fourier or wavelet transform and image processing is reported.
Index Terms—Image processing, defect detection, forged metal.
The authors are with Niigata University, Niigata, Japan (e-mail: yamazaki@ie.niigata-u.ac.jp, f17c033e@mail.cc.niigata-u.ac.jp).
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Cite: Tatsuya Yamazaki and Akito Fukui, "Defect Detection for Forged Metal Parts by Image Processing," International Journal of Future Computer and Communication vol. 9, no. 1, pp. 23-26, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
(CC BY 4.0).
