Laser & Optoelectronics Progress, Volume. 59, Issue 22, 2215003(2022)

Defect Detection of Wheel Set Tread Based on Improved YOLOv5

Yaoze Sun1、* and Junwei Gao2
Author Affiliations
  • 1School of Automation, Qingdao University, Qingdao 266071, Shandong, China
  • 2Shandong Key Laboratory of Industrial Control Technology, Qingdao 266071, Shandong, China
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    References(19)

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

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    [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).

    [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).

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    Yaoze Sun, Junwei Gao. Defect Detection of Wheel Set Tread Based on Improved YOLOv5[J]. Laser & Optoelectronics Progress, 2022, 59(22): 2215003

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    Paper Information

    Category: Machine Vision

    Received: Dec. 15, 2021

    Accepted: Jan. 11, 2022

    Published Online: Oct. 13, 2022

    The Author Email: Yaoze Sun (486695900@qq.com)

    DOI:10.3788/LOP202259.2215003

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