Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm
The quality of weld joints is a pivotal factor influencing the strength and structural reliability for mechanical parts. Difficulties in identification caused by weld joint adhesion and defects, such as missing weld joints, this paper designs an efficient welded joint detection system, which utilize...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10829943/ |
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| author | Lingjiang Guo Yong Yan Junjie Cui Zhongsi Xu |
| author_facet | Lingjiang Guo Yong Yan Junjie Cui Zhongsi Xu |
| author_sort | Lingjiang Guo |
| collection | DOAJ |
| description | The quality of weld joints is a pivotal factor influencing the strength and structural reliability for mechanical parts. Difficulties in identification caused by weld joint adhesion and defects, such as missing weld joints, this paper designs an efficient welded joint detection system, which utilizes Otsu threshold segmentation and morphological processing methods to achieve the initial segmentation of the welded joint region. Furthermore, the contour of the weld joint is extracted with greater accuracy by random incremental algorithm, which contributes to accelerating the following the detection speed only considering the weld joint region. Subsequently, watershed algorithm based on distance transformation is adopted to segment each weld joint precisely. Considering defect localization, the edge features of the missing weld region are identified and separated using the difference calculation method. The results demonstrate that the system could accurately segment adhesive weld joints and identify missing weld joint locations with the variation of the workpiece positions and angles, fully satisfying the real-time detection requirement during the weld quality identification. |
| format | Article |
| id | doaj-art-1adf61e8621544b5bc76e4d97788ec81 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-1adf61e8621544b5bc76e4d97788ec812025-01-15T00:02:23ZengIEEEIEEE Access2169-35362025-01-01136869687710.1109/ACCESS.2025.352672810829943Research on Weld Identification and Defect Localization Based on an Improved Watershed AlgorithmLingjiang Guo0Yong Yan1https://orcid.org/0000-0001-6065-1081Junjie Cui2Zhongsi Xu3College of Mechatronics Engineering, North University of China, Taiyuan, Shanxi, ChinaCollege of Mechatronics Engineering, North University of China, Taiyuan, Shanxi, ChinaCollege of Mechatronics Engineering, North University of China, Taiyuan, Shanxi, ChinaCollege of Mechatronics Engineering, North University of China, Taiyuan, Shanxi, ChinaThe quality of weld joints is a pivotal factor influencing the strength and structural reliability for mechanical parts. Difficulties in identification caused by weld joint adhesion and defects, such as missing weld joints, this paper designs an efficient welded joint detection system, which utilizes Otsu threshold segmentation and morphological processing methods to achieve the initial segmentation of the welded joint region. Furthermore, the contour of the weld joint is extracted with greater accuracy by random incremental algorithm, which contributes to accelerating the following the detection speed only considering the weld joint region. Subsequently, watershed algorithm based on distance transformation is adopted to segment each weld joint precisely. Considering defect localization, the edge features of the missing weld region are identified and separated using the difference calculation method. The results demonstrate that the system could accurately segment adhesive weld joints and identify missing weld joint locations with the variation of the workpiece positions and angles, fully satisfying the real-time detection requirement during the weld quality identification.https://ieeexplore.ieee.org/document/10829943/Weld spot recognition and defect localizationOtsu threshold segmentationmissing weld area detectionwatershed algorithm |
| spellingShingle | Lingjiang Guo Yong Yan Junjie Cui Zhongsi Xu Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm IEEE Access Weld spot recognition and defect localization Otsu threshold segmentation missing weld area detection watershed algorithm |
| title | Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm |
| title_full | Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm |
| title_fullStr | Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm |
| title_full_unstemmed | Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm |
| title_short | Research on Weld Identification and Defect Localization Based on an Improved Watershed Algorithm |
| title_sort | research on weld identification and defect localization based on an improved watershed algorithm |
| topic | Weld spot recognition and defect localization Otsu threshold segmentation missing weld area detection watershed algorithm |
| url | https://ieeexplore.ieee.org/document/10829943/ |
| work_keys_str_mv | AT lingjiangguo researchonweldidentificationanddefectlocalizationbasedonanimprovedwatershedalgorithm AT yongyan researchonweldidentificationanddefectlocalizationbasedonanimprovedwatershedalgorithm AT junjiecui researchonweldidentificationanddefectlocalizationbasedonanimprovedwatershedalgorithm AT zhongsixu researchonweldidentificationanddefectlocalizationbasedonanimprovedwatershedalgorithm |