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The size distribution and fragmentation level of the blasted rock mass are crucial factors in enhancing the efficiency of loading, transportation, crushing, and milling processes. This article provides a comparative analysis of grain size distribution curves derived from image analysis using various methods. The first method compares representative fragments of the muck pile through manual analysis, commercial software, and an Open-Source Algorithm. The second method evaluates the grain size distribution curves of the entire muck pile, utilizing both commercial software and an open-source algorithm.
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145--162
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
autor
- Wroclaw University of Science and Technology, Faculty of Geoengineering, Mining and Geology, Department of Mining, Na Grobli 15, 50-421 Wroclaw, Poland
autor
- SSE POLSKA SP. Z O.O., Rogów Sobócki, ul. Wrocławska 58, 55-050 Sobótka
autor
- „Poltegor-Instytut” Institute of Opencast Mining, 51-616 Wrocław, Poland
Bibliografia
- AMOAKO R., JHA A., ZHONG S., 2022, Rock Fragmentation Prediction Using an Artificial Neural Network and Support Vector Regression Hybrid Approach, Mining, 2, 233–247, https://doi.org/10.3390/mining2020013
- BHATAWDEKAR R.M., KUMAR R., SABRI SABRI M.M., ROY B., MOHAMAD E.T., KUMAR D., KWON S., 2023, Estimating Flyrock Distance Induced Due to Mine Blasting by Extreme Learning Machine Coupled with an Equilibrium Optimizer, Sustainability, 15, 3265, https://doi.org/10.3390/su15043265
- DING X., JAMEI M., HASANIPANAH M., ABDULLAH R.A., LE B.N., 2023, Optimized Data-Driven Models for Prediction of Flyrock due to Blasting in Surface Mines, Sustainability, 15, 8424, https://doi.org/10.3390/su15108424
- DOTTO M.S., POURRAHIMIAN Y., 2024, The Influence of Explosive and Rock Mass Properties on Blast Damage in a Single-Hole Blasting, Mining, 4, 168–188, https://doi.org/10.3390/mining4010011
- DUMAKOR-DUPEY N.K., ARYA S., JHA A., 2021, Advances in Blast-Induced Impact Prediction – A Review of Machine Learning Applications, Minerals, 11, 601.
- ENGIN I.C., MAERZ N.H., BOYKO K.J. et al., 2020, Practical Measurement of Size Distribution of Blasted Rocks Using LiDAR Scan Data, Rock Mech. Rock Eng., 53, 4653–4671, https://doi.org/10.1007/s00603-020-02181-5
- ESEN S., BILGIN H.A., 2000, Effect of explosive on fragmentation, The 4th Drilling and Blasting Symposium.
- FIGUEIREDO J., TORRES V., CRUZ R., MOREIRA D., 2023, Blasting Fragmentation Study Using 3D Image Analysis of a Hard Rock Mine, Appl. Sci., 13, 7090, https://doi.org/10.3390/app13127090
- IKEDA H., SATO T., YOSHINO K., TORIYA H., JANG H., ADACHI T., KITAHARA I., KAWAMURA Y., 2023, Deep Learning-Based Estimation of Muckpile Fragmentation Using Simulated 3D Point Cloud Data, Appl. Sci., 13, 10985, https://doi.org/10.3390/app131910985
- ISHEYSKIY V., SANCHIDRIÁN J.A., 2020, Prospects of Applying MWD Technology for Quality Management of Drilling and Blasting Operations at Mining Enterprises, Minerals, 10, 925, https://doi.org/10.3390/min10100925
- KAWALEC W., KRÓL R., SUCHORAB N., SZYMAŃSKI M., 2019, The analysis and assessment of grain size distribution on the example of a chosen granite mine. In: World Multidisciplinary Earth Sciences Symposium (WMESS 2019), IOP Publishing, art. 012113, s. 1–8, DOI:10.1088/17551315/362/1/012113.
- LI P.F., XIE S.D., XIA H.P., WANG D.K., XU Z.Y., 2023, Advanced analysis of blast pile fragmentation in open-pit mining utilizing 3D point cloud technology, Traitement du Signal, Vol. 40, No. 6, pp. 2507–2519, https://doi.org/10.18280/ts.400615
- MCKEE I., IL D.J., 2013, Understanding Mine to Mill, Cooperative Research Centre for Optimizing Resource Extraction. The Cooperative Research Centre for Optimising Resource Extraction CRC ORE: Brisbane, Australia, ISBN 978-1-922029-27-0.
- MULENGA S., 2020, Evaluation of Factors Influencing Rock fragmentation by Blasting using Interrelations Diagram Method, Journal of Physical Sciences, 2020, 2 (1), 1–15, https://doi.org/10.47941/jps.382
- NANDA S., PAL B.K., 2020, Analysis of blast fragmentation using WipFrag, J. Image, 5 (6).
- NANDA S., NAIK H.K.A., 2023, Review of the Blast Fragmentation Analysis Techniques used in Surface Mines, Journal of Mines, Metals and Fuels, 71 (12), 2445–2454, https://doi.org/10.18311/jmmf/2023/28601
- NIKKHAH A., VAKYLABAD A.B., HASSANZADEH A., NIEDOBA T., SUROWIAK A., 2022, An evaluation of the impact of ore fragmented by blasting on mining performance, Minerals, 12, 258.
- NIKKHAH A., VAKYLABAD A.B., HASSANZADEH A., NIEDOBA T., SUROWIAK A., 2022, An Evaluation on the Impact of Ore Fragmented by Blasting on Mining Performance, Minerals, 12, 258, https://doi.org/10.3390/min12020258
- OUCHTERLONY F., 2005, The Swebrec function: linking fragmentation by blasting and crushing, Mining Technology (Trans. Inst. Min. Metall. A), Vol. 114, pp. 29–44.
- OUCHTERLONY F., SANCHIDRIÁN J.A., 2019, A Review of Development of Better Prediction Equations for Blast Fragmentation, J. Rock Mech. Geotech. Eng., 11, 1094–1109.
- PAL ROY P., 2021, Emerging trends in drilling and blasting technology: concerns and commitments, Arab. J. Geosci., 14, 652, https://doi.org/10.1007/s12517-021-06949-z
- PENG J., CUI Y., ZHONG Z., AN Y., 2023, Ore Rock Fragmentation Calculation Based on Multi-Modal Fusion of Point Clouds and Images, Appl. Sci., 13, 12558, https://doi.org/10.3390/app132312558
- SHARMA M., SINGH B., CHOUDHARY B., RAINA A., KHANDELWAL M., RUKHIYAR S., 2024, Prediction of rock fragmentation in a fiery seam of an open-pit coal mine in India, Journal of Rock Mechanics and Geotechnical Engineering, pp. 2879–2893. ISSN 1674-7755, https://doi.org/10.1016/j.jrmge.2023.11.047.
- STOJANOVIC M., LAPČEVIĆ V., VELJKO IVICA L., VOJINOVIĆ V., 2023, Analysis of blast frag-mentation using WipFrag. In: The 54th International October Conference on Mining and Metallurgy, 18–21 October 2023, Bor Lake, Serbia, 68–71.
- VU T., BAO T., HOANG Q.V., DREBENSTETD C., HOA P.V., THANG H.H., 2021, Measuring blast fragmentation at Nui Phao open-pit mine, Vietnam using the Mask R-CNN deep learning model, Min. Technol., 130, 232–243. https://doi.org/10.1080/25726668.2021.1944458
- YOSHINO K., SATO T., TORIYA H., SHISHIDO H., HYONGDOO J., KAWAMURA Y., KITAHARA I., 2022, An Estimation Method of Fragmentation in Blast Muckpiles using Local and Global Modules of Deep Learning Based on 3D Point Clouds, International Journal of the Society of Materials Engineering for Resources, 25 (1), 78–84, https://doi.org/10.5188/ijsmer.25.78
- ZEGGEREN F.V., CHUNG S.H., 1975, A model for the prediction of fragmentation, pattern and costs in rock blasting. In: Proceedings of 15th symposium on rock mechanics, American Society of Civil Engineers, New York, pp. 557–567.
- ZHIRONKIN S., EZDINA N., 2023, Review of Transition from Mining 4.0 to Mining 5.0 Innovative Technologies, Appl. Sci., 13, 4917, https://doi.org/10.3390/app13084917
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-57786699-adca-4b19-a1f5-7aa7e7da9b5a
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