Identification approaches for steel strip surface defects in hot rolling Process
In steel manufacturing process, flat products are greatly concerned with the surface quality and the possibilities of its on-line inspection. The visual control is obviously unable to continuously check the surface of the moving product, and the control at the ending stage remains not suitable alth...
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| Format: | Article |
| Language: | English |
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University "Hassiba Benbouali" de Chlef
2023-01-01
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| Series: | Revue Nature et Technologie |
| Subjects: | |
| Online Access: | http://193.194.82.220/index.php/natec/article/view/127 |
| _version_ | 1797404840321613824 |
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| author | Zoheir MENTOURI Abdelkrim MOUSSAOUI Djalil BOUDJEHEM Adel BOUDIAF Slimane ZIANI |
| author_facet | Zoheir MENTOURI Abdelkrim MOUSSAOUI Djalil BOUDJEHEM Adel BOUDIAF Slimane ZIANI |
| author_sort | Zoheir MENTOURI |
| collection | DOAJ |
| description |
In steel manufacturing process, flat products are greatly concerned with the surface quality and the possibilities of its on-line
inspection. The visual control is obviously unable to continuously check the surface of the moving product, and the control at the ending stage remains not suitable although, it may provide information about process trends and parameters history. So, strip surface defects that are not detected yield to product downgrading or to costly rework operations for producer and/or end users. With such needed quality level, steel surface inspection systems are more and more implemented for detecting defects and allowing correction at appropriate time. Based on Computer vision, these applications make a use of detection and classification algorithms to identify these arising defects. The present work is related to a Project of a scientific and economic impact: The Development of an on-line inspection system for strip surface defects identification during the thermo-mechanical treatment in hot rolling process. We asses, in this work, some approaches in labeling each of the defects belonging to a database created for this aim. This Dataset is compound of five, among the most frequent, surface defect types and with 108 variants of each one. Obtained results shown the importance of the choice of a relevant image features extractor.
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| first_indexed | 2024-03-09T03:00:51Z |
| format | Article |
| id | doaj.art-497176432eec44339b0e99be7de4df97 |
| institution | Directory Open Access Journal |
| issn | 1112-9778 2437-0312 |
| language | English |
| last_indexed | 2024-03-09T03:00:51Z |
| publishDate | 2023-01-01 |
| publisher | University "Hassiba Benbouali" de Chlef |
| record_format | Article |
| series | Revue Nature et Technologie |
| spelling | doaj.art-497176432eec44339b0e99be7de4df972023-12-04T16:22:59ZengUniversity "Hassiba Benbouali" de ChlefRevue Nature et Technologie1112-97782437-03122023-01-011001Identification approaches for steel strip surface defects in hot rolling ProcessZoheir MENTOURI0Abdelkrim MOUSSAOUI1Djalil BOUDJEHEM2Adel BOUDIAF3Slimane ZIANI4a Laboratory of Advanced Control (LABCAV), University of May 8th 1945, Guelma, Algeria / b Research Center in Industrial Technologies (CRTI), BP64, Chéraga 16014, Algiers, AlgeriaLaboratory of Electrical Engineering (LGEG), University of May 8th 1945, Guelma, AlgeriaLaboratory of Advanced Control (LABCAV), University of May 8th 1945, Guelma, AlgeriaResearch Center in Industrial Technologies (CRTI), BP64, Chéraga 16014, Algiers, AlgeriaResearch Center in Industrial Technologies (CRTI), BP64, Chéraga 16014, Algiers, Algeria In steel manufacturing process, flat products are greatly concerned with the surface quality and the possibilities of its on-line inspection. The visual control is obviously unable to continuously check the surface of the moving product, and the control at the ending stage remains not suitable although, it may provide information about process trends and parameters history. So, strip surface defects that are not detected yield to product downgrading or to costly rework operations for producer and/or end users. With such needed quality level, steel surface inspection systems are more and more implemented for detecting defects and allowing correction at appropriate time. Based on Computer vision, these applications make a use of detection and classification algorithms to identify these arising defects. The present work is related to a Project of a scientific and economic impact: The Development of an on-line inspection system for strip surface defects identification during the thermo-mechanical treatment in hot rolling process. We asses, in this work, some approaches in labeling each of the defects belonging to a database created for this aim. This Dataset is compound of five, among the most frequent, surface defect types and with 108 variants of each one. Obtained results shown the importance of the choice of a relevant image features extractor. http://193.194.82.220/index.php/natec/article/view/127Computer visionDetection & ClassificationRolling processQuality & Surface defects |
| spellingShingle | Zoheir MENTOURI Abdelkrim MOUSSAOUI Djalil BOUDJEHEM Adel BOUDIAF Slimane ZIANI Identification approaches for steel strip surface defects in hot rolling Process Revue Nature et Technologie Computer vision Detection & Classification Rolling process Quality & Surface defects |
| title | Identification approaches for steel strip surface defects in hot rolling Process |
| title_full | Identification approaches for steel strip surface defects in hot rolling Process |
| title_fullStr | Identification approaches for steel strip surface defects in hot rolling Process |
| title_full_unstemmed | Identification approaches for steel strip surface defects in hot rolling Process |
| title_short | Identification approaches for steel strip surface defects in hot rolling Process |
| title_sort | identification approaches for steel strip surface defects in hot rolling process |
| topic | Computer vision Detection & Classification Rolling process Quality & Surface defects |
| url | http://193.194.82.220/index.php/natec/article/view/127 |
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