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Study on signs of defects in the image of the surface of flat-rolled products

О. С. ЛогуноваMagnitogorsk State Technical University named after G. I. Nosov, 455000 Magnitogorsk, RussiaPalvan KalandarovTashkent Institute of Irrigation and Agricultural Mechanization Engineers, 100000 Tashkent, UzbekistanEvgeny GarbarMagnitogorsk State Technical University named after G. I. Nosov, 455000 Magnitogorsk, RussiaMakhmud AbdullaevTashkent State Technical University, 100095 Tashkent, UzbekistanN. B. AlimovaTashkent State Technical University, 100095 Tashkent, UzbekistanO MatchanovTashkent Institute of Irrigation and Agricultural Mechanization Engineers, 100000 Tashkent, UzbekistanKhusniddin AbdullaevTashkent Institute of Irrigation and Agricultural Mechanization Engineers, 100000 Tashkent, Uzbekistan
E3S Web of Conferencesjournal2021en
ABI

Аннотация

Currently, more and more challenges of modern industrial enterprises require an increase in the reliability of the information on the quality of products. This becomes possible when using digital technologies to assess the quality of products. The cited publication discusses the technology for recognizing defects in the surface of sheet products in images obtained from cameras of the strip inspection system during rolling. The authors proposed a classification of the signs of defects in the image and highlighted the most significant of them also suggested using geometric, optical and spectral features for images of flat-rolled products containing defects of different classes. The research results at this stage, obtained during the processing of digital images, showed that to identify a defect and reduce false-positive and false-negative alarms of the automated defect identification system, it is required to conduct a study of interval estimates and make decision-making rules based on intersection and merging of intervals; introduce additional classes that allow the introduction of signs that characterize the irregularity of the shape of defects and the characteristic location; the use of new technologies of soft computing will reveal the hidden patterns of the manifestation of defects in the images of the surface of the steel strip.

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