Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5
In the realm of railroad transportation, the switch sliding baseplate constitutes one of the most crucial components within railroad crossings. Wear defects occurring on the switch sliding baseplate can give rise to issues such as delayed switch operation, inflexible switching, or even complete fail...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Lubricants |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4442/12/12/422 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850050002761547776 |
|---|---|
| author | Qing Jiang Ruipeng Gao Yan Zhao Wenzhen Yu Zhuofan Dang Shiyi Deng |
| author_facet | Qing Jiang Ruipeng Gao Yan Zhao Wenzhen Yu Zhuofan Dang Shiyi Deng |
| author_sort | Qing Jiang |
| collection | DOAJ |
| description | In the realm of railroad transportation, the switch sliding baseplate constitutes one of the most crucial components within railroad crossings. Wear defects occurring on the switch sliding baseplate can give rise to issues such as delayed switch operation, inflexible switching, or even complete failure, thereby escalating the risk of train derailment. Consequently, the detection of wear defects on the switch sliding baseplate is of paramount importance for enhancing traffic efficiency and guaranteeing the safety of train switching operations. Micro-cutting defects, which are among the most significant defects resulting from wear, exhibit complex and diverse morphological and characteristic features. Traditional random sampling methods struggle to capture their detailed characteristics, leading to inadequate accuracy and robustness in the detection process. To address the above-mentioned issues, the YOLOv5s algorithm has been refined and subsequently applied to the detection of micro-cutting defects generated by wear on the switch sliding baseplate. The experimental results demonstrate that, in comparison with the currently prevalent mainstream target detection algorithms, the improved model can attain optimal recall rates R, mAP@0.5, and mAP@0.5:0.95. Specifically, when contrasted with the original YOLOv5s algorithm, the improved model witnesses significant enhancements in its precision rate P, the recall rate R, mAP@0.5, and mAP@0.5:0.95, with increments of 1.26%, 5.6%, 9.1%, and 8.92%, respectively. These improvements fully corroborate the performance of the proposed model in the context of micro-cutting defect detection. |
| format | Article |
| id | doaj-art-dfaaa1fd8bff4871b5b2785c2753e65c |
| institution | DOAJ |
| issn | 2075-4442 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Lubricants |
| spelling | doaj-art-dfaaa1fd8bff4871b5b2785c2753e65c2025-08-20T02:53:34ZengMDPI AGLubricants2075-44422024-11-01121242210.3390/lubricants12120422Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5Qing Jiang0Ruipeng Gao1Yan Zhao2Wenzhen Yu3Zhuofan Dang4Shiyi Deng5School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaState Key Laboratory for Mechanical Behavior of Materials, School of Materials Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaState Key Laboratory for Mechanical Behavior of Materials, School of Materials Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaIn the realm of railroad transportation, the switch sliding baseplate constitutes one of the most crucial components within railroad crossings. Wear defects occurring on the switch sliding baseplate can give rise to issues such as delayed switch operation, inflexible switching, or even complete failure, thereby escalating the risk of train derailment. Consequently, the detection of wear defects on the switch sliding baseplate is of paramount importance for enhancing traffic efficiency and guaranteeing the safety of train switching operations. Micro-cutting defects, which are among the most significant defects resulting from wear, exhibit complex and diverse morphological and characteristic features. Traditional random sampling methods struggle to capture their detailed characteristics, leading to inadequate accuracy and robustness in the detection process. To address the above-mentioned issues, the YOLOv5s algorithm has been refined and subsequently applied to the detection of micro-cutting defects generated by wear on the switch sliding baseplate. The experimental results demonstrate that, in comparison with the currently prevalent mainstream target detection algorithms, the improved model can attain optimal recall rates R, mAP@0.5, and mAP@0.5:0.95. Specifically, when contrasted with the original YOLOv5s algorithm, the improved model witnesses significant enhancements in its precision rate P, the recall rate R, mAP@0.5, and mAP@0.5:0.95, with increments of 1.26%, 5.6%, 9.1%, and 8.92%, respectively. These improvements fully corroborate the performance of the proposed model in the context of micro-cutting defect detection.https://www.mdpi.com/2075-4442/12/12/422switch sliding baseplatewear and tearmicro-cutting defectsscanning electron microscopeYOLOv5 |
| spellingShingle | Qing Jiang Ruipeng Gao Yan Zhao Wenzhen Yu Zhuofan Dang Shiyi Deng Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 Lubricants switch sliding baseplate wear and tear micro-cutting defects scanning electron microscope YOLOv5 |
| title | Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 |
| title_full | Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 |
| title_fullStr | Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 |
| title_full_unstemmed | Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 |
| title_short | Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 |
| title_sort | research on a wear defect detection method for a switch sliding baseplate based on improved yolov5 |
| topic | switch sliding baseplate wear and tear micro-cutting defects scanning electron microscope YOLOv5 |
| url | https://www.mdpi.com/2075-4442/12/12/422 |
| work_keys_str_mv | AT qingjiang researchonaweardefectdetectionmethodforaswitchslidingbaseplatebasedonimprovedyolov5 AT ruipenggao researchonaweardefectdetectionmethodforaswitchslidingbaseplatebasedonimprovedyolov5 AT yanzhao researchonaweardefectdetectionmethodforaswitchslidingbaseplatebasedonimprovedyolov5 AT wenzhenyu researchonaweardefectdetectionmethodforaswitchslidingbaseplatebasedonimprovedyolov5 AT zhuofandang researchonaweardefectdetectionmethodforaswitchslidingbaseplatebasedonimprovedyolov5 AT shiyideng researchonaweardefectdetectionmethodforaswitchslidingbaseplatebasedonimprovedyolov5 |