A Method for Reconstruction of Size Distributions from 3D Drone Image Analysis: A Case Study

Pablo Segarra1, José A. Sanchidrián1, Markus Pötsch2, Luis Iglesias1, Santiago Gómez1, Andreas Gaich2, Maurizio Bernardini1
1Universidad Politécnica de Madrid – ETSI Minas y Energía, Madrid, Spain
23GSM GmbH, Graz, Austria

Tóm tắt

This paper describes a novel procedure to assess fragmentation from automatic analysis of 3D photogrammetric models with a commercial software. The muckpiles from 12 blasts were photographed with a conventional drone to build 3D photogrammetric models; the flights were made with a relatively constant ground sampling distance (GSD) of 6.2 sd 0.92 mm (mean and standard deviation, respectively). A comparison with already published mass-based size distributions from 11 of these blasts, shows a good performance of automatic 3D-fragmentation measurements in the coarse range (P ≥ 60%), while deviations between mass-based and 3D model fragmentation analysis grow towards the central-fines range. As a solution, the Swebrec function is fitted to the reliable part of the size distributions, well above the GSD, and then is extended towards the fines, down to a percentage passing of 5–10%. The suitable fitting range is obtained iteratively from the mass-based fragmentation data; the lower fragment size considered is independent of the model’s resolution (i.e. GSD) with mean of 357 mm (equivalent to a passing in the range 66–86%, and well above the GSD of our models). The resulting distributions match properly mass-based size distributions with relative errors in percentile sizes of 15.5 sd 3.4%, and they can be represented with the simplest form of the fragmentation-energy-fan. As a guideline for reconstruction of size distributions and fines assessment when mass-based data is not available, the lower-fitting limit of 357 mm yields reasonable results (mean errors in pass in the range 5–36%) for the present case. The errors are limited enough to keep a sound description of the variation of fragmentation with change in blast design.

Từ khóa


Tài liệu tham khảo

3GSM, 2021. BlastMetriX UAV®; Version 4.1.2 Bamford T, Esmaieli K, Schoellig AP (2018) Evaluation of UAV System accuracy for automated fragmentation measurement. In: Schunnesson H, Johansson D (eds) Proceedings of 12th international symposium on rock fragmentation by blasting, Luleå, Sweden, June 11–13, Luleå Tekniska Universitet, Luleå, pp 715–730 Campbell AD, Thurley MJ (2017) Application of laser scanning to measure fragmentation in underground mines. Min Technol 126:240–327. https://doi.org/10.1080/14749009.2017.1296668 CloudCompare (2017) CloudCompare, Version 2.8.1 (http://www.Cloudcompare.org) Cunningham CVB (1983) The Kuz-Ram model for prediction of fragmentation from blasting. In: Holmberg R, Rustan A (eds) Proceedings of 1st international symposium on rock fragmentation by blasting, Luleå, Sweden, 22–26 August. Luleå Tekniska Universitet, Luleå, pp 439–453 Cunningham CVB (1987) Fragmentation estimations and the Kuz-Ram model—four years on. In: Fourney WL, Dick RD (eds) Proceedings of 2nd international symposium on rock fragmentation by blasting, Keystone, CO, 23–26 August. Society of Experimental Mechanics, Bethel, pp 475–487 Eden DJ, Franklin JA (1996) Disintegration, fusion and edge net fidelity. In: Franklin JA, Katsabanis T (eds) Proceedings of the FRAGBLAST 5 workshop on measurement of blast fragmentation, Montreal, Canada, 23–24 August, pp 127–132 Gaich A, Pötsch M, Rieder B, Schubert W (2019) Drone imagery for the acquisition and assessment of rock fall areas. In: Proceedings of the 14th ISRM congress on rock mechanics and rock engineering, Foz do Iguaçu, Brazil, 13–18 September, paper 15036. International Society for Rock Mechanics and Rock Engineering Gaich A, Pötsch M, Baumgartner M (2022) Automatic 3D fragmentation analysis from drone imagery. In: Proceedings of the 48th annual research symposium on explosives and blasting technique, Las Vegas, NV, 30 January–2 February, paper 1685. International Society of Explosives Engineers Jang H, Kitahara I, Kawamura Y, Endo Y, Topal E, Degawa R, Mazara S (2020) Development of 3D rock fragmentation measurement system using photogrammetry. Int. J. Mining. Reclam Environ 34:294–305. https://doi.org/10.1080/17480930.2019.1585597 Kemeny JM (1994) Practical technique for determining the size distribution of blasted benches waste dump and heap leach sites. Min Eng 46(11):1281–1284 Kleine TH, Cameron AR (1996) Blast fragmentation measurement using Goldsize. In: Franklin JA, Katsabanis T (eds) Proceedings of the FRAGBLAST 5 workshop on measurement of blast fragmentation, Montreal, QC, Canada, 23–24 August, pp 83–89 Kuznetsov VM (1973) The mean diameter of the fragments formed by blasting rock. Soviet Mining Sci 9:144–148 Maerz NH, Palangio TC, Franklin, JA (1996) The Wipfrag image based granulometry system. In: Franklin JA, Katsabanis T (eds) Proceedings of the FRAGBLAST 5 workshop on measurement of blast fragmentation, Montreal, QC, Canada, 23–24 August, pp 91–98 Olsson M, Svahn V, Ouchterlony F, Bergqvist I (2003) Rock fragmentation in quarries. SveBeFo report 60, Swedish Rock Engineering Research, Stockholm (in Swedish) Oñederra I, Thurley MJ, Catalan A (2014) Measuring blast fragmentation at Esperanza mine using high-resolution 3D laser scanning. Min Technol 124:34–36. https://doi.org/10.1179/1743286314Y.0000000076 Otterness RE, Stagg MS, Rholl SA, Smith NS (1991) Correlation of shot design parameters to fragmentation. In: Proceedings of 7th annual research symposium on explosives and blasting technique. ISEE, Solon, pp 179–190 Ouchterlony F (2005) The Swebrec© function: linking fragmentation by blasting and crushing. Min Technol 114(1):29–44. https://doi.org/10.1179/037178405X44539 Ouchterlony F (2009) Fragmentation characterization; the Swebrec function and its use in blast engineering. In: Sanchidrián JA (ed) Proceedings 9th international symposium on rock fragmentation by blasting. CRC Press, Boca Raton, FL, pp 3–22 Ouchterlony F, Sanchidrián JA (2018) The fragmentation-energy fan concept and the Swebrec function in modeling drop weight testing. Rock Mech Rock Eng 51(10):3129–3156. https://doi.org/10.1007/s00603-018-1458-5 Ouchterlony F, Sanchidrián JA, Moser P (2017) Percentile fragment size predictions for blasted rock and the fragmentation–energy fan. Rock Mech Rock Eng 50(4):751–779. https://doi.org/10.1007/s00603-016-1094-x Ouchterlony F, Olsson M, Nyberg U, Potts G, Andersson P, Gustavsson L (2005) Optimal fragmentering i krosstäker—Fältförsök Vändletäkten. Report 1:11, MinBas Project, Stockholm (in Swedish) Ouchterlony F, Nyberg U, Olsson M, Vikström K, Svedensten P, Bergskolan i Filipstad (2010) Optimal fragmentering i krosstäkter, fältförsök i Långåsen. Swebrec report 2010:2. Swedish Blasting Research Centre, Luleå University of Technology (in Swedish) Ouchterlony F, Nyberg U, Olsson M, Widenberg K, Svedensten P (2015) Effects of specific charge and electronic delay detonators on fragmentation in an aggregate quarry—building fragmentation model design curves. In: Spathis AT et al (eds) Proceedings of 11th international symposium on rock fragmentation by blasting (Fragblast 11). The Australasian Institute of Mining and Metallurgy, Carlton, pp 727–739 Rosato AD, Blackmore DL, Zhang N, Lan Y (2002) A perspective on vibration-induced size segregation of granular materials. Chem Eng Sci 57:265–275. https://doi.org/10.1016/S0009-2509(01)00380-3 Sanchidrián JA, Ouchterlony F (2018) A distribution-free description of fragmentation by blasting based on dimensional analysis. Rock Mech Rock Eng 50(4):781–806. https://doi.org/10.1007/s00603-016-1131-9 Sanchidrián JA, Ouchterlony F, Moser P, Segarra P, López LM (2012) Performance of some distributions to describe rock fragmentation data. Int J Rock Mech Min Sci 53:18–31. https://doi.org/10.1016/j.ijrmms.2012.04.001 Sanchidrián JA, Ouchterlony F, Segarra P, Moser P (2014) Size distribution functions for rock fragments. Int J Rock Mech Min Sci 71:381–394. https://doi.org/10.1016/j.ijrmms.2014.08.007 Sanchidrián JA, Segarra P, Ouchterlony F, Gómez S (2022) The influential role of powder factor vs. other variables in full-scale blasting: a perspective through the fragment size-energy fan. Rock Mech Rock Eng 55(7):4209–4236. https://doi.org/10.1007/s00603-022-02856-1 Sanchidrián JA (2015) Ranges of validity of some distribution functions for blast-fragmented rock. In: Fragblast 11, Proceeding of 11th international symposium on rock fragmentation by blasting. AusIMM, Carlton, pp 741–748 Segarra P, Sanchidrián JA, Navarro J, Castedo R (2018) The fragmentation energy-fan model in quarry blasts. Rock Mech Rock Eng 51(7):2175–2190. https://doi.org/10.1007/s00603-018-1470-9 Snavely N, Seitz SM, Szeliski R (2008) Modeling the world from internet photo collections. Int J Comput Vision 80(2):189–210. https://doi.org/10.1007/s11263-007-0107-3 Tamir R, Wagner M, Campbell J, Dakers N (2017) Utilization of aerial drones to optimize blast and stockpile fragmentation. J Explos Eng 34:6–15 Thurley M (2013) Automated image segmentation and analysis of rock piles in an open-pit mine. In: International conference on digital image computing: techniques and applications (DICTA 2013), Hobart, Australia, 26–28 November 2013, vol 8, 6691484, Piscataway, NJ, IEEE Thurley MJ (2014) Measuring the visible particles for automated online particle size distribution estimation. In: Proceedings of the XXVII international mineral processing congress: IMPC 2014, 20–24 October 2014, Santiago, Chile Thurley M, Fernandez A, Segarra P (2018) Fragmentation monitoring of Run-of-mine (ROM)‒report 2: Blasts 7–11. SLIM technical report, European Union’s Horizon 2020 research and innovation programme under grant agreement no. 730294. Luleå University of Technology Toriya H, Tungol ZPL, Ikeda H, Owada N, Jang HD, Adachi T, Kitahara I, Kawamura Y (2022) Fragmentation size distribution measurement by GNSS-aided photogrammetry at real mine site. Mining 2(3):438–448. https://doi.org/10.3390/mining2030023 Westoby MJ, Brasington J, Glasser NF, Hambrey MJ, Reynolds JM (2012) Structure-from-Motion’photogrammetry: a low-cost, effective tool for geoscience applications. Geomorphology 179:300–314. https://doi.org/10.1016/j.geomorph.2012.08.021