High-Speed Railway Fastener Detection Algorithm Based on Improved Faster R-CNN
CSTR:
Author:
Affiliation:

Clc Number:

U213;TP39

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Aiming at deflection or loss of high-speed railway fasteners caused by the loose fasteners in the ballastless track of high-speed railway, this paper proposes a high-speed railway fastener detection algorithm based on improved Faster R-CNN. Deformable convolution was introduced in the feature extraction network to build deformable residual convolution block(DRCB), which makes the feature extraction process more focused on the fastener region and achieves the accurate extraction of fastener state; and Alpha-IoU was used as the target regression loss function to improve the regression accuracy of high-speed railway fasteners. The experimental results show that the algorithm proposed improves the detection accuracy of high-speed railway fasteners and can perform fastener localization and state detection more accurately than other algorithms.

    Reference
    Related
    Cited by
Get Citation

裴莹玲,罗晖,张诗慧,李佳敏,徐杰.基于改进Faster R-CNN的高铁扣件检测算法[J].华东交通大学学报英文版,2023,40(1):75-81.
Pei Yingling, Luo Hui, Zhang Shihui, Li Jiamin, Xu Jie. High-Speed Railway Fastener Detection Algorithm Based on Improved Faster R-CNN[J]. JOURNAL OF EAST CHINA JIAOTONG UNIVERSTTY,2023,40(1):75-81

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: February 23,2023
  • Published:
Article QR Code