A review of laser scanning for geological and geotechnical applications in underground mining

被引:44
作者
Singh, Sarvesh Kumar [1 ]
Banerjee, Bikram Pratap [1 ,2 ]
Raval, Simit [1 ]
机构
[1] Univ New South Wales, Sch Minerals & Energy Resources Engn, Sydney, NSW 2052, Australia
[2] Agr Victoria, Grains Innovat Pk, Horsham, Vic 3400, Australia
关键词
Mine automation; Point cloud; Rock mass characterisation; Change detection; Data registration; Georeferencing; POINT CLOUDS; SIMULTANEOUS LOCALIZATION; DISCONTINUITY ORIENTATION; ROCK DISCONTINUITIES; COAL-MINES; LIDAR; FRACTURE; TUNNELS; REGISTRATION; INTEGRATION;
D O I
10.1016/j.ijmst.2022.09.022
中图分类号
TD [矿业工程];
学科分类号
0819 ;
摘要
Laser scanning can provide timely assessments of mine sites despite adverse challenges in the operational environment. Although there are several published articles on laser scanning, there is a need to review them in the context of underground mining applications. To this end, a holistic review of laser scanning is presented including progress in 3D scanning systems, data capture/processing techniques and primary applications in underground mines. Laser scanning technology has advanced significantly in terms of mobility and mapping, but there are constraints in coherent and consistent data collection at certain mines due to feature deficiency, dynamics, and environmental influences such as dust and water. Studies suggest that laser scanning has matured over the years for change detection, clearance measurements and structure mapping applications. However, there is scope for improvements in lithology identification, surface parameter measurements, logistic tracking and autonomous navigation. Laser scanning has the potential to provide real-time solutions but the lack of infrastructure in underground mines for data transfer, geodetic networking and processing capacity remain limiting factors. Nevertheless, laser scanners are becoming an integral part of mine automation thanks to their affordability, accuracy and mobility, which should support their widespread usage in years to come. (c) 2023 Published by Elsevier B.V. on behalf of China University of Mining & Technology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:133 / 154
页数:22
相关论文
共 183 条
  • [1] Factors Influencing Stope Hanging Wall Stability and Ore Dilution in Narrow-Vein Deposits: Part 1
    Abdellah, Wael R. Elrawy
    Hefni, Mohammed A.
    Ahmed, Haitham M.
    [J]. GEOTECHNICAL AND GEOLOGICAL ENGINEERING, 2020, 38 (02) : 1451 - 1470
  • [2] Ahmed S, 2017, P 1 INT C UNDERGROUN, P467
  • [3] Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances
    Alarifi, Abdulrahman
    Al-Salman, AbdulMalik
    Alsaleh, Mansour
    Alnafessah, Ahmad
    Al-Hadhrami, Suheer
    Al-Ammar, Mai A.
    Al-Khalifa, Hend S.
    [J]. SENSORS, 2016, 16 (05)
  • [4] Amedjoe CG, 2015, J GEOL MIN RES, V7, P19, DOI 10.5897/jgmr2014.0215
  • [5] Role of Deep Learning in Loop Closure Detection for Visual and Lidar SLAM: A Survey
    Arshad, Saba
    Kim, Gon-Woo
    [J]. SENSORS, 2021, 21 (04) : 1 - 17
  • [6] Horizontal single hole blast testing-Part 1: Systematic measurements using TLS surveys
    Aubertin, Jonathan D.
    Hutchinson, D. Jean
    Diederichs, Mark
    [J]. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2021, 114
  • [7] Geometrical heterogeneity of the joint roughness coefficient revealed by 3D laser scanning
    Bao, Han
    Zhang, Guobiao
    Lan, Hengxing
    Yan, Changgen
    Xu, Jiangbo
    Xu, Wei
    [J]. ENGINEERING GEOLOGY, 2020, 265
  • [8] Battulwar Rushikesh, 2020, Advances in Visual Computing. 15th International Symposium, ISVC 2020. Proceedings. Lecture Notes in Computer Science (LNCS 12510), P718, DOI 10.1007/978-3-030-64559-5_57
  • [9] A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models
    Battulwar, Rushikesh
    Zare-Naghadehi, Masoud
    Emami, Ebrahim
    Sattarvand, Javad
    [J]. JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING, 2021, 13 (04) : 920 - 936
  • [10] Baylis CNC, 2020, MOBILE DRONE LIDAR S, P325