Abstract
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.
Highlights
Cold-rolled steel with subsequent annealing and galvanized coating is used in industry for the manufacture of car bodies, housings for household appliances and the construction industry
The quality of the metal surface is one of the key criteria for the consumers [1].When assessing the surface quality, both organoleptic methods and automated systems for recognizing surface defects (ASRSD) are used that analyze images of the rolled surface obtained at the sections of the, such as a continuous galvanizing aggregate(ACG) and a continuous hot-dip galvanizing aggregate(AHG) of PJSC Magnitogorsk Iron and Steel Works "(PJSC" MMK ") ASRDP, used in production, structurally consist of sensors, network interfaces, a defect detection unit, a database [2] (Fig. 1)
The result of the work of the ASRSD is a set of digital images that are subjected to automated processing
Summary
Cold-rolled steel with subsequent annealing and galvanized coating is used in industry for the manufacture of car bodies, housings for household appliances and the construction industry. The quality of the metal surface is one of the key criteria for the consumers [1].When assessing the surface quality, both organoleptic methods and automated systems for recognizing surface defects (ASRSD) are used that analyze images of the rolled surface obtained at the sections of the , such as a continuous galvanizing aggregate(ACG) and a continuous hot-dip galvanizing aggregate(AHG) of PJSC Magnitogorsk Iron and Steel Works "(PJSC" MMK ") ASRDP, used in production, structurally consist of sensors, network interfaces, a defect detection unit, a database [2] (Fig. 1). A false determination of the class of defect does not allow making a timely corrective action on the unit or on previous production redistributions. It is essential for eliminating the shortcomings to develop a more accurate method for assessing the quality of the strip surface. In [8], the features of images are considered for further use of features in the classification of a defect
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