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Automated Discontinuity Extraction Software Versus Manual Virtual Discontinuity Mapping: Performance Evaluation in Rock Mass Characterization and Rockfall Hazard Identification

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Abstract

Ground control failures are one of the main causes of accidents in the underground stone mining industry. Some of the fundamental tools for rockfall hazard identification are related to rock mass characterization and geotechnical discontinuity mapping. Recent technological advances in these methods are related to remote sensing techniques and point cloud processing software for automated discontinuity mapping. Remote sensing techniques, such as LiDAR and photogrammetry, generate multi-million point clouds with millimetric precision, capturing the structure of the rock mass. The automated point cloud processing tools offer alternative algorithm-based methods to characterize and map these discontinuities. However, their applicability is constrained by multiple factors such as site specific conditions of the rock mass and the parameters used within the mapping algorithms. This paper evaluates the performance of automated discontinuity extraction software compared with manual virtual discontinuity mapping. Sampling windows from laser-scanned sections in an underground limestone mine are defined and mapped using discontinuity set extractor (DSE). Results from the virtual discontinuity software are compared with manually extracted fractures from I-Site based on reviewing orientation, trace length, spacing, number of extracted discontinuities, and processing time. The analysis determined that the automated mapping algorithm was able to identify the same discontinuity sets that had been manually mapped. The automated mapping software mapped an excessive amount of smaller fractures, which caused the comparison of both mapping techniques to be unsuccessful in terms of trace length and spacing.

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Acknowledgements

The authors would like to thank Lhoist mining engineers and management for their support and guidance during this project. MAPTEK is acknowledged for providing a license of the software I-Site Studio.

Funding

This work is funded by the NIOSH Mining Program under Contract No. 200-2016-91300. Views expressed here are those of the authors and do not necessarily represent those of any funding source.

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Authors and Affiliations

  1. Mining and Minerals Engineering Department, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA

    Juan J. Monsalve, Alex Pfreundschuh, Aman Soni & Nino Ripepi

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  1. Juan J. Monsalve
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  2. Alex Pfreundschuh
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  3. Aman Soni
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  4. Nino Ripepi
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Correspondence to Juan J. Monsalve.

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Monsalve, J.J., Pfreundschuh, A., Soni, A. et al. Automated Discontinuity Extraction Software Versus Manual Virtual Discontinuity Mapping: Performance Evaluation in Rock Mass Characterization and Rockfall Hazard Identification. Mining, Metallurgy & Exploration 38, 1383–1394 (2021). https://doi.org/10.1007/s42461-021-00416-9

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