Bolt loosening angle measurement along full range of screw exposure length based on 3D point cloud

被引:1
|
作者
Li, Shengyuan [1 ]
Le, Yushan [1 ]
Gao, Jiachen [1 ]
Li, Xian [1 ]
Zhao, Xuefeng [2 ]
机构
[1] China Univ Min & Technol, Sch Mech & Civil Engn, Xuzhou 221116, Peoples R China
[2] Dalian Univ Technol, Sch Infrastruct Engn, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
Bolt group; Bolt loosening angle measurement; Screw exposure length; 3D point cloud; BEHAVIOR;
D O I
10.1016/j.autcon.2024.105785
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The existing two-dimensional (2D) vision-based bolt loosening measurement range is generally limited to 0-60 degrees. degrees To overcome this limitation, a bolt loosening angle measurement method along full range of screw exposure length based on three-dimensional (3D) point cloud is proposed. Initially, 3D point clouds of bolt groups were reconstructed using 2D images under 18 working conditions, and the 3D point cloud of a single bolt was extracted from the bolt group. Subsequently, the bolt loosening angle along full range of screw exposure length was measured by calculating the rotation angle derived from the change in screw exposure length before and after loosening. The average relative error of all bolt loosening angle measurement results under the 18 working conditions was 3.46 %. Finally, the factors influencing the proposed method were analyzed. The results demonstrated that the proposed method could accurately measure the bolt loosening angle along full range of screw exposure length.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] Improvement of 3D reconstruction based on a new 3D point cloud filtering algorithm
    Soulaiman El Hazzat
    Mostafa Merras
    Signal, Image and Video Processing, 2023, 17 : 2573 - 2582
  • [32] Improvement of 3D reconstruction based on a new 3D point cloud filtering algorithm
    El Hazzat, Soulaiman
    Merras, Mostafa
    SIGNAL IMAGE AND VIDEO PROCESSING, 2023, 17 (05) : 2573 - 2582
  • [33] Rigid 3D Point Cloud Registration Based on Point Feature Histograms
    Wang, Xi
    Zhang, Xutang
    PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MACHINERY, ELECTRONICS AND CONTROL SIMULATION (MECS 2017), 2017, 138 : 543 - 550
  • [34] Reconstruction of a 3D point moving along a line under a varying focal length
    Hu, ML
    Sun, L
    Wei, S
    2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS, 2003, : 2835 - 2839
  • [35] New technology on 3d point cloud by laser measurement of various platforms
    Satoh T.
    Yotsumata T.
    Mano K.
    Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering, 2019, 85 (03): : 223 - 227
  • [36] Point Cloud Quality Assessment via 3D Edge Similarity Measurement
    Lu, Zian
    Huang, Hailiang
    Zeng, Huanqiang
    Hou, Junhui
    Ma, Kai-Kuang
    IEEE SIGNAL PROCESSING LETTERS, 2022, 29 : 1804 - 1808
  • [37] 3D position angle measurement based on a lens array
    Du Ming-xin
    Yan Yu-feng
    Zhang Ran
    Cai Cun-liang
    Yu Xin
    Bai Su-ping
    Yu Yang
    CHINESE OPTICS, 2022, 15 (01): : 45 - 55
  • [38] Fast outlier removing method for point cloud of microscopic 3D measurement based on social circle
    Cui, Haihua
    Wang, Qianjin
    Dong, Dengfeng
    Wei, Hao
    Zhang, Yihua
    MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2020, 17 (06) : 8138 - 8151
  • [39] Complex Building Laser Measurement Modelling Based on Intelligently Computed 3D Point Cloud Data
    Xue, Ting
    Zou, Ji-Cai
    Huang, Sharina
    Journal of Network Intelligence, 2024, 9 (02): : 1179 - 1195
  • [40] Error compensation of the multi-visual structured light 3D measurement system based on 3D point cloud for accuracy consistency
    Shi, Rongjun
    Huang, Junhui
    Wang, Zhao
    Qi, Miaowei
    Gao, Jianmin
    TWELFTH INTERNATIONAL CONFERENCE ON INFORMATION OPTICS AND PHOTONICS (CIOP 2021), 2021, 12057