American Journal of Civil Engineering

Research Article | | Peer-Reviewed |

A Method for Detecting the Spacing of Steel Arch Frames in Construction Tunnels Based on Three-Dimensional Laser Technology

Received: 15 October 2023    Accepted: 7 November 2023    Published: 13 November 2023
Views:       Downloads:

Share This Article

Abstract

The present invention provides a point cloud spacing extraction algorithm for tunnel steel arch frames. This method first calculates the angle between the point cloud of the tunnel steel arch construction section and the adjacent coordinate axis and rotates it so that its axial direction is parallel to the adjacent coordinate axis. Then, the point cloud axial normal vector is calculated, and a threshold is set based on the calculated normal vector to extract the steel arch point cloud. Then, a clustering algorithm is used to extract the single steel arch point cloud, Use the C2C-Distance method based on the kd tree to calculate the closest distance from each point in a single steel arch point cloud to another single steel arch. Take the average value to obtain the distance between the tunnel steel arches, fit the single arch point cloud, fit a spatial circular point cloud, calculate the difference between the single point cloud and the spatial circular point cloud, and extract the excessively distorted part in the single point cloud. This method has good robustness and is suitable for various working conditions of tunnels. It can effectively extract point clouds of steel arch frames and obtain point cloud spacing with millimeter level errors, making it suitable for monitoring tunnel construction quality.

DOI 10.11648/j.ajce.20231104.11
Published in American Journal of Civil Engineering (Volume 11, Issue 4, July 2023)
Page(s) 40-43
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Point Cloud, Normal Vector, Euclidean Clustering, Steel Arch Frames, Tunnel

References
[1] Wei Tengyuan. Analysis of the deformation characteristics of steel arch support in a soft rock highway tunnel [J]. Architectural Technology, 2023, 54 (17): 2099-2102.
[2] Sun Senzhen, Jing Liujie, Wang Li. Detection and extraction of tunnel steel arch using probability features of point cloud spatial projection [J]. Surveying and Mapping Bulletin, 2023 (06): 129-133.
[3] Tang Jing. Research on Steel Arch Locking Construction Technology for Soft and Broken Surrounding Rock Tunnel [J]. Science and Technology Innovation, 2023 (13): 104-107.
[4] Xing Ying, Song Tao, Zhao Yan, et al. A point cloud simplification algorithm combining 3D SIFT feature extraction and voxel filtering [J]. Laser Journal, 2023, 44 (03): 163-169.
[5] Wei Shuo, Zhao Nanxiang, Li Minle, et al. Single photon denoising algorithm combining improved DBSCAN and statistical filtering [J]. Laser Technology, 2021, 45 (05): 601-606.
[6] Liu Chunsong, Song Wei, Luo Yinsheng, et al. An improved point cloud image denoising method with advantages of radius filtering and RANSAC [J]. Laser Journal, 2022, 43 (03): 92-97.
[7] Tu Haowen, Ding Zhao, Zhou Hua, et al. Thresholding segmentation algorithm for 3D point cloud targets based on RANSAC [J]. Microprocessor, 2022, 43 (06): 24-27.
[8] Ma Xuelei, Xue Heru. Point cloud normal vector estimation method based on iterative least squares [J]. Computer Simulation, 2023, 40 (07): 363-367.
[9] Song Shuya. Point Cloud Segmentation Method Based on Improved Euclidean Clustering [J]. Metrology and Testing Technology, 2022, 49 (05): 96-100.
[10] Song Jian, Wang Xinya, Tang Zhiqiang, et al. Research on non-uniform point cloud plane segmentation based on improved region growth [J]. Modern Transportation Technology, 2023, 20 (02): 42-48.
[11] Xu Wang, Guan Yunlan, Zhang Zhao, et al. Airborne LiDAR asymptotic morphological filtering algorithm combined with thin plate spline interpolation [J]. Progress in Laser and Optoelectronics, 2022, 59 (10): 412-421.
[12] Zhao Junyi, Ma Jun, Chen Shouhong, et al. Scene oriented kd-tree point cloud filtering algorithm [J]. Laser Journal, 2021, 42 (11): 74-78.
[13] Ma Jie, Wang Xujiao, Ma Pengfei, et al. A Deep Learning Point Cloud Classification Network Based on KD Tree Neighborhood Query [J]. Journal of Shenzhen University (Science and Engineering Edition), 2020, 37 (01): 79-83.
[14] Lan Yiling, Kang Chuanli, Wang Ning, et al. Moving Least Squares Method with Additional Value Added Conditions for Point Cloud Hole Repair [J]. Infrared and Laser Engineering, 2023, 52 (02): 414-423.
[15] Wang Peng, Xin Peikang, Liu Yin, et al. Extracting the Center Coordinates of Point Cloud Nodes in Reticulated Shell Structures Using Least Squares Method [J/OL]. Journal of Graphics: 1-9 [2023-10-31].
Cite This Article
  • APA Style

    Ma, C., Luo, H., Wang, C., Lv, G. (2023). A Method for Detecting the Spacing of Steel Arch Frames in Construction Tunnels Based on Three-Dimensional Laser Technology. American Journal of Civil Engineering, 11(4), 40-43. https://doi.org/10.11648/j.ajce.20231104.11

    Copy | Download

    ACS Style

    Ma, C.; Luo, H.; Wang, C.; Lv, G. A Method for Detecting the Spacing of Steel Arch Frames in Construction Tunnels Based on Three-Dimensional Laser Technology. Am. J. Civ. Eng. 2023, 11(4), 40-43. doi: 10.11648/j.ajce.20231104.11

    Copy | Download

    AMA Style

    Ma C, Luo H, Wang C, Lv G. A Method for Detecting the Spacing of Steel Arch Frames in Construction Tunnels Based on Three-Dimensional Laser Technology. Am J Civ Eng. 2023;11(4):40-43. doi: 10.11648/j.ajce.20231104.11

    Copy | Download

  • @article{10.11648/j.ajce.20231104.11,
      author = {Chuanyi Ma and Hongzheng Luo and Chuan Wang and Gaohang Lv},
      title = {A Method for Detecting the Spacing of Steel Arch Frames in Construction Tunnels Based on Three-Dimensional Laser Technology},
      journal = {American Journal of Civil Engineering},
      volume = {11},
      number = {4},
      pages = {40-43},
      doi = {10.11648/j.ajce.20231104.11},
      url = {https://doi.org/10.11648/j.ajce.20231104.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajce.20231104.11},
      abstract = {The present invention provides a point cloud spacing extraction algorithm for tunnel steel arch frames. This method first calculates the angle between the point cloud of the tunnel steel arch construction section and the adjacent coordinate axis and rotates it so that its axial direction is parallel to the adjacent coordinate axis. Then, the point cloud axial normal vector is calculated, and a threshold is set based on the calculated normal vector to extract the steel arch point cloud. Then, a clustering algorithm is used to extract the single steel arch point cloud, Use the C2C-Distance method based on the kd tree to calculate the closest distance from each point in a single steel arch point cloud to another single steel arch. Take the average value to obtain the distance between the tunnel steel arches, fit the single arch point cloud, fit a spatial circular point cloud, calculate the difference between the single point cloud and the spatial circular point cloud, and extract the excessively distorted part in the single point cloud. This method has good robustness and is suitable for various working conditions of tunnels. It can effectively extract point clouds of steel arch frames and obtain point cloud spacing with millimeter level errors, making it suitable for monitoring tunnel construction quality.
    },
     year = {2023}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - A Method for Detecting the Spacing of Steel Arch Frames in Construction Tunnels Based on Three-Dimensional Laser Technology
    AU  - Chuanyi Ma
    AU  - Hongzheng Luo
    AU  - Chuan Wang
    AU  - Gaohang Lv
    Y1  - 2023/11/13
    PY  - 2023
    N1  - https://doi.org/10.11648/j.ajce.20231104.11
    DO  - 10.11648/j.ajce.20231104.11
    T2  - American Journal of Civil Engineering
    JF  - American Journal of Civil Engineering
    JO  - American Journal of Civil Engineering
    SP  - 40
    EP  - 43
    PB  - Science Publishing Group
    SN  - 2330-8737
    UR  - https://doi.org/10.11648/j.ajce.20231104.11
    AB  - The present invention provides a point cloud spacing extraction algorithm for tunnel steel arch frames. This method first calculates the angle between the point cloud of the tunnel steel arch construction section and the adjacent coordinate axis and rotates it so that its axial direction is parallel to the adjacent coordinate axis. Then, the point cloud axial normal vector is calculated, and a threshold is set based on the calculated normal vector to extract the steel arch point cloud. Then, a clustering algorithm is used to extract the single steel arch point cloud, Use the C2C-Distance method based on the kd tree to calculate the closest distance from each point in a single steel arch point cloud to another single steel arch. Take the average value to obtain the distance between the tunnel steel arches, fit the single arch point cloud, fit a spatial circular point cloud, calculate the difference between the single point cloud and the spatial circular point cloud, and extract the excessively distorted part in the single point cloud. This method has good robustness and is suitable for various working conditions of tunnels. It can effectively extract point clouds of steel arch frames and obtain point cloud spacing with millimeter level errors, making it suitable for monitoring tunnel construction quality.
    
    VL  - 11
    IS  - 4
    ER  - 

    Copy | Download

Author Information
  • Shandong HI-Speed Group, Jinan, China

  • School of Oilu Transportation, Shandong University, Jinan, China

  • Shandong HI-Speed Group, Jinan, China

  • School of Oilu Transportation, Shandong University, Jinan, China

  • Sections