Defect Detection of Wheel Set Tread Based on Improved YOLOv5

Yaoze Sun; Junwei Gao

doi:10.3788/LOP202259.2215003

[1] Cong T, Han J M, Zhang G Z et al. Analysis of micro damage factors of shattered rim and tread shelling of railway wheel[J]. China Railway Science, 38, 93-99(2017).

[2] Jin X S, Liu Q Y[M]. Tribology of wheel and rail(2004).

[3] Hou T, Zhang Z T. Improve the application of the Canny algorithm in the detection of wheel tread damage[J]. Journal of Railway Science and Engineering, 15, 2107-2112(2018).

[4] Lü H B. Research on damaged tread detection of train wheel set under machine vision[D](2017).

[5] Zong D G, Mei J S, Jiang Y N. Research on the locomotive wheel to follow-type flaw detection system[J]. Electronic Measurement Technology, 41, 128-132(2018).

[6] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

[7] Redmon J, Farhadi A. YOLO9000: better, faster, stronger[C], 6517-6525(2017).

[8] Lai W H, Zhou M R, Wang J G et al. Fast location of coal gangue based on multispectral band selection[J]. Chinese Journal of Lasers, 48, 1611001(2021).

[9] Liu W, Anguelov D, Erhan D et al. SSD: single shot MultiBox detector[M]. Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, 9905, 21-37(2016).

[10] Guo R H, Zhang L, Yang Y et al. X-ray image controlled knife detection and recognition based on improved SSD[J]. Laser & Optoelectronics Progress, 58, 0404001(2021).

[11] Fan L L, Zhao H W, Zhao H Y et al. Survey of target detection based on deep convolutional neural networks[J]. Optics and Precision Engineering, 28, 1152-1164(2020).

[12] Xiao H P. Wheel tread damage detection based on deep learning[D](2019).

[13] He J, Yu H Y, Zhang C F et al. Damage detection of train wheelset tread using Canny-YOLOv3[J]. Journal of Electronic Measurement and Instrumentation, 33, 25-30(2019).

[14] Zhang L, Huang D P, Liao S P et al. Wheelset tread defect detection method based on target detection network[J]. Laser & Optoelectronics Progress, 58, 0410020(2021).

[15] Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934

[16] Li B, Wang C, Wu J et al. Surface defect detection of aeroengine components based on improved YOLOv4 algorithm[J]. Laser & Optoelectronics Progress, 58, 1415004(2021).

[17] Lin T Y, Dollár P, Girshick R et al. Feature pyramid networks for object detection[C], 936-944(2017).

[18] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer Vision-ECCV 2018. Lecture notes in computer science, 11211, 3-19(2018).

[19] Zhang Y F, Ren W Q, Zhang Z et al. Focal and efficient IOU loss for accurate bounding box regression[EB/OL]. https://arxiv.org/abs/2101.08158