CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute Mechanism
The catenary is an important part of the railway power supply system, and the good health of its key components is an important condition for the operation of high-speed trains. Due to the complex composition of catenary components and the large size difference between components, it is very difficu...
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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/10535473/ |
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| author | Shuai Xu Jiyou Fei Geng Zhao Xiaodong Liu Hua Li |
| author_facet | Shuai Xu Jiyou Fei Geng Zhao Xiaodong Liu Hua Li |
| author_sort | Shuai Xu |
| collection | DOAJ |
| description | The catenary is an important part of the railway power supply system, and the good health of its key components is an important condition for the operation of high-speed trains. Due to the complex composition of catenary components and the large size difference between components, it is very difficult to implement the locating and detection of all components. It severely limits the subsequent failure analysis of catenary components. Aiming at the problem of the difficult locating of multiple components, this paper proposes a catenary complex component locating method based on the improved YOLO algorithm named CCL-YOLO. Firstly, based on the YOLO baseline method, a framework for locating complex components of railway catenary is proposed, which achieves the accurate locating of 40 catenary components and paves the way for subsequent defect detection. Furthermore, a novel “Gather-and-Distribute” mechanism is introduced, which improves the original feature fusion method and its global feature fusion capability and effectively improves the locating accuracy of complex catenary components. In addition, the Wasserstein distance loss is also applied to improve the detection capability of small objects. Finally, the comprehensive experimental results show that the proposed method for locating complex components of railway catenary can achieve a mean average precision of 94.1% for 40 components of different sizes. Meanwhile, it reduces the number of parameters and the complexity of the algorithm to a certain extent, thus paving the way for subsequent fault detection, which is of important application value. |
| format | Article |
| id | doaj-art-2276fa34a57244729c69c1da7d5aeaf8 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-2276fa34a57244729c69c1da7d5aeaf82025-01-21T00:02:12ZengIEEEIEEE Access2169-35362025-01-01139064907210.1109/ACCESS.2024.340371610535473CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute MechanismShuai Xu0https://orcid.org/0009-0004-6004-7158Jiyou Fei1https://orcid.org/0000-0003-2547-8783Geng Zhao2Xiaodong Liu3Hua Li4College of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaCollege of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaCollege of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaCollege of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaCollege of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaThe catenary is an important part of the railway power supply system, and the good health of its key components is an important condition for the operation of high-speed trains. Due to the complex composition of catenary components and the large size difference between components, it is very difficult to implement the locating and detection of all components. It severely limits the subsequent failure analysis of catenary components. Aiming at the problem of the difficult locating of multiple components, this paper proposes a catenary complex component locating method based on the improved YOLO algorithm named CCL-YOLO. Firstly, based on the YOLO baseline method, a framework for locating complex components of railway catenary is proposed, which achieves the accurate locating of 40 catenary components and paves the way for subsequent defect detection. Furthermore, a novel “Gather-and-Distribute” mechanism is introduced, which improves the original feature fusion method and its global feature fusion capability and effectively improves the locating accuracy of complex catenary components. In addition, the Wasserstein distance loss is also applied to improve the detection capability of small objects. Finally, the comprehensive experimental results show that the proposed method for locating complex components of railway catenary can achieve a mean average precision of 94.1% for 40 components of different sizes. Meanwhile, it reduces the number of parameters and the complexity of the algorithm to a certain extent, thus paving the way for subsequent fault detection, which is of important application value.https://ieeexplore.ieee.org/document/10535473/Railways catenarycomponent locationYOLOgather-and-distributeWasserstein distance loss |
| spellingShingle | Shuai Xu Jiyou Fei Geng Zhao Xiaodong Liu Hua Li CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute Mechanism IEEE Access Railways catenary component location YOLO gather-and-distribute Wasserstein distance loss |
| title | CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute Mechanism |
| title_full | CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute Mechanism |
| title_fullStr | CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute Mechanism |
| title_full_unstemmed | CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute Mechanism |
| title_short | CCL-YOLO: Catenary Components Location Based on YOLO and Gather-Distribute Mechanism |
| title_sort | ccl yolo catenary components location based on yolo and gather distribute mechanism |
| topic | Railways catenary component location YOLO gather-and-distribute Wasserstein distance loss |
| url | https://ieeexplore.ieee.org/document/10535473/ |
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