Automated ground support deformation monitoring: a novel method with new opportunities for geotechnical engineers

Authors: Franke, J; Gonzalez, C Download Paper Open access courtesy of:

DOI https://doi.org/10.36487/ACG_repo/2325_04

Cite As:
Franke, J & Gonzalez, C 2023, 'Automated ground support deformation monitoring: a novel method with new opportunities for geotechnical engineers', in J Wesseloo (ed.), Ground Support 2023: Proceedings of the 10th International Conference on Ground Support in Mining, Australian Centre for Geomechanics, Perth, pp. 75-90, https://doi.org/10.36487/ACG_repo/2325_04



Abstract:
One of the regular tasks of geotechnical and mining engineers is the measurement and management of ground deformation in underground excavations. Although other methods have historically been used to do so, light detection and ranging (LiDAR) has emerged as the most suitable technology for this application because it caters for quantitative and omission-free rather than merely qualitative tracking. Regular scanning has shown it to be highly advantageous for mines with swelling or squeezing ground, and those with rapid deformation. Despite the LiDAR potential for tracking underground mining voids, its adoption has been slow because associated conventional data processing is time consuming and requires training, upskilling, and devotion by geotechnical engineers. This often becomes a bottleneck to bringing this method into use. Our paper introduces a new solution of fully automated LiDAR point cloud data processing dedicated to void deformation tracking that not only enables geotechnical engineers to avoid having to learn unrelated skills, but also provides immediate output of sophisticated reporting deliverables. This opens up the opportunity to monitor many more excavations at a higher frequency and gain much better insights than is possible with conventional manual processing tools and methodology. Secondly, this paper presents how this new processing methodology utilises cloud-based data storage and processing infrastructure that allows onsite users to become independent of local IT constraints and to avoid otherwise applicable limitations in storage and viewing of what are very large files. Critically, automatically generated 3D files for localised deformation assessment, as well as automatically generated summary reports presenting key deformation tracking analysis outcomes to decision makers, facilitate the detection and understanding of:

Keywords: LiDAR, automation, convergence monitoring, automated point cloud processing, instrumentation and monitoring

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