Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas Pipeline
Accurate welding defect detection (WDD) of Oil/Gas pipelines (OGP) is an active and challenging task in the reliability engineering of OGPs. To solve the problems that U-Net cannot effectively extract multi-scale global context details of the image by simple skip connection, and small defects cannot...
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| Format: | Article |
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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/10811901/ |
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| author | Shanwen Zhang Xuqi Wang Ting Zhang |
| author_facet | Shanwen Zhang Xuqi Wang Ting Zhang |
| author_sort | Shanwen Zhang |
| collection | DOAJ |
| description | Accurate welding defect detection (WDD) of Oil/Gas pipelines (OGP) is an active and challenging task in the reliability engineering of OGPs. To solve the problems that U-Net cannot effectively extract multi-scale global context details of the image by simple skip connection, and small defects cannot be accurately detected, a WDD method of OGP by combining residual-dilated-Inception U-Net (RDIU-Net) and Transformer (RDIUTrans) is proposed. In the model, RDIU-Net is used to extract the multi-scale local features, and Transformer is utilized to model multi-scale global contextual relationships and spatial dependency. Compared with U-Net and its variants, RDIUTrans can extract the global feature and local detail features for WDD. The results on the welding defect image dataset show that RDIUTrans is effective for WDIS with the segmentation accuracy of 95.34%. It is suitable for WDD scenes with various welding defects. |
| format | Article |
| id | doaj-art-8965a6cc7ffa4fd2ad7c10cf2d4d1884 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-8965a6cc7ffa4fd2ad7c10cf2d4d18842025-01-14T00:02:43ZengIEEEIEEE Access2169-35362025-01-01135437544510.1109/ACCESS.2024.352122010811901Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas PipelineShanwen Zhang0Xuqi Wang1https://orcid.org/0000-0001-7375-2535Ting Zhang2School of Electronic Information, Xijing University, Xi’an, ChinaSchool of Electronic Information, Xijing University, Xi’an, ChinaSchool of Electronic Information, Xijing University, Xi’an, ChinaAccurate welding defect detection (WDD) of Oil/Gas pipelines (OGP) is an active and challenging task in the reliability engineering of OGPs. To solve the problems that U-Net cannot effectively extract multi-scale global context details of the image by simple skip connection, and small defects cannot be accurately detected, a WDD method of OGP by combining residual-dilated-Inception U-Net (RDIU-Net) and Transformer (RDIUTrans) is proposed. In the model, RDIU-Net is used to extract the multi-scale local features, and Transformer is utilized to model multi-scale global contextual relationships and spatial dependency. Compared with U-Net and its variants, RDIUTrans can extract the global feature and local detail features for WDD. The results on the welding defect image dataset show that RDIUTrans is effective for WDIS with the segmentation accuracy of 95.34%. It is suitable for WDD scenes with various welding defects.https://ieeexplore.ieee.org/document/10811901/Welding defect detectionresidual-dilated-inception U-NettransformerRDIU-Net and transformer |
| spellingShingle | Shanwen Zhang Xuqi Wang Ting Zhang Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas Pipeline IEEE Access Welding defect detection residual-dilated-inception U-Net transformer RDIU-Net and transformer |
| title | Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas Pipeline |
| title_full | Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas Pipeline |
| title_fullStr | Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas Pipeline |
| title_full_unstemmed | Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas Pipeline |
| title_short | Combining Multi-Scale U-Net With Transformer for Welding Defect Detection of Oil/Gas Pipeline |
| title_sort | combining multi scale u net with transformer for welding defect detection of oil gas pipeline |
| topic | Welding defect detection residual-dilated-inception U-Net transformer RDIU-Net and transformer |
| url | https://ieeexplore.ieee.org/document/10811901/ |
| work_keys_str_mv | AT shanwenzhang combiningmultiscaleunetwithtransformerforweldingdefectdetectionofoilgaspipeline AT xuqiwang combiningmultiscaleunetwithtransformerforweldingdefectdetectionofoilgaspipeline AT tingzhang combiningmultiscaleunetwithtransformerforweldingdefectdetectionofoilgaspipeline |