Real-time analysis of particle size distribution of rocks using a domestic software and hardware complex
A.V. Dremin1, S.V. Sitdikova2, V.S. Velikanov2, 3, D.S. Stozhkov2, I.A. Grishin4
1 DAVTECH LLC, Ekaterinburg, Russian Federation
2 Ural State Mining University, Ekaterinburg, Russian Federation
3 Ural State Agrarian University, Ekaterinburg, Russian Federation
4 Magnitogorsk State Technical University, Magnitogorsk, Russian Federation
Russian Mining Industry №3 / 2025 p.118-123
Abstract: Economic performance of all the major technological processes in mining of mineral deposits is significantly affected by the particle size distribution of the rock mass. Particle size distribution of the muck pile, which is termed as “fragmentation” in foreign literature, determines the efficiency and productivity of technological processes of mining. It is known that when blasted the rocks form a number of lumps of various shapes and sizes, and a variety of characteristics have been proposed to assess them. The proposed characteristics of the rock mass as a statistical system can be divided into two classes. The first class includes characteristics that define individual properties of individual lumps, while the second class comprises characteristics that describe the integral properties of the system. Measurement of the particle size distribution of large volumes of rocks in the muck pile poses a serious challenge. This paper discusses general issues in analysing fragmentation in terms of reliability and promptness of assessment, as well as the available methods used to evaluate the blast results. Results are presented on recognition of the rock fragments using digital methods, and the importance of accurate determination of the lump size in image analysis is identified.
Keywords: particle size distribution, minerals, muck pile, photoplanimetric method, rock lumpiness
Acknowledgements: This work was financially supported by the Ministry of Science and Higher Education of the Russian Federation (Project FRZU-2023–0008).
For citation: Dremin A.V., Sitdikova S.V., Velikanov V.S., Stozhkov D.S., Grishin I.A. Real-time analysis of particle size distribution of rocks using a domestic software and hardware complex. Russian Mining Industry. 2025;(3):118–123. (In Russ.) https://doi.org/10.30686/1609-9192-2025-3-118-123
Article info
Received: 05.03.2025
Revised: 18.04.2025
Accepted: 21.04.2025
Information about the authors
Aleksandr V. Dremin – Director General, DAVTECH LLC, Ekaterinburg, Russian Federation
Svetlana V. Sitdikova – Senior Lecturer, Department of Automatics and Computer Technologies, Ural State Mining University, Ekaterinburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Vladimir S. Velikanov – Dr. Sci. (Eng.), Professor, Department of Automatics and Computer Technologies, Ural State Mining University, Ekaterinburg, Russian Federation; Professor, Department of Mathematics and Information Technologies, Ural State Agrarian University, Ekaterinburg, Russian Federation; https://orcid.org/0000-0001-5581-2733; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Dmitry S. Stozhkov – Cand. Sci. (Eng.), Associate Professor, Department of Electrical Engineering, Ural State Mining University, Ekaterinburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Igor A. Grishin – Cand. Sci. (Eng.), Head of the Department of Geology, Mine Surveying and Mineral Processing, Magnitogorsk State Technical University, Magnitogorsk, Russian Federation; https://orcid.org/0000-0001-8010-7542; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
References
1. Барон Л.И. Кусковатость и методы ее измерения. М.: Изд-во АН СССР; 1960. 123 с. Режим доступа: https://www.geokniga.org/books/32278 (дата обращения: 11.03.2025).
2. Барон Л.И., Граубиц Ж.К. Линейный и точечный методы определения кусковатости по фотопланограммам. Известия Карельского и Кольского филиалов Академии наук СССР. 1958;(3):107–115. Baron L.I., Graubits Zh.K. Линейный и точечный методы определения кусковатости по фотопланограммам. Izvestiya Karelskogo i Kolskogo Filialov Akademii Nauk SSSR. 1958;(3):107–115. (In Russ.)
3. Дремин А.В., Великанов В.С. К вопросу о гранулометрическом составе взорванных скальных пород. Горная промышленность. 2023;(4):73–78. https://doi.org/10.30686/1609-9192-2023-4-73-78 Dremin A.V., Velikanov V.S. Regarding the particle-size composition of blasted rocks. Russian Mining Industry. 2023;(4):73–78. https://doi.org/10.30686/1609-9192-2023-4-73-78
4. Парамонов Г.П., Лисевич В.В. Прогнозирование параметров развала горной массы при производстве взрывных работ. Международный научно-исследовательский журнал. 2016;(4-6):100–103. Режим доступа: https://research-journal.org/archive/4-46-2016-april/prognozirovanie-parametrov-razvala-gornoj-massy-pri-proizvodstve-vzryvnyx-rabot (дата обращения: 28.02.2025). Paramonov G.P., Lisevich V.V. Forecasting of parameters of a rock mass collapse when blasting work. International Research Journal. 2016;(4-6):100–103. Available at: https://research-journal.org/archive/4-46-2016-april/prognozirovanie-parametrovrazvala-gornoj-massy-pri-proizvodstve-vzryvnyx-rabot (accessed: 28.02.2025).
5. Угольников В.К., Симонов П.С., Угольников Н.В. Прогнозирование гранулометрического состава взорванной горной массы. Горный информационно-аналитический бюллетень. 2007;(S7):63–70. Ugolnikov V.K., Simonov P.S., Ugolnikov N.V. Forecasting of particle size distribution of blasted rock mass. Mining Informational and Analytical Bulletin. 2007;(S7):63–70. (In Russ.).
6. Гавришев С.Е., Калмыков В.Н., Пикалов В.А., Караулов Н.Г., Угольников Н.В. Разработка рекомендаций по регулированию кусковатости строительных горных пород при взрывном разрушении. Горная промышленность. 2025;(1):58–63. https://doi.org/10.30686/1609-9192-2025-1-58-63 Gavrishev S.E., Kalmykov V.N., Pikalov V.A., Karaulov N.G., Ugolnikov N.V. Development of recommendations for controlling the lump size of construction rocks during blasting. Russian Mining Industry. 2025;(1):58–63. (In Russ.) https://doi.org/10.30686/1609-9192-2025-1-58-63
7. Singh B.K., Mondal D., Shahid M., Saxena A., Roy P.N.S. Application of digital image analysis for monitoring the behavior of factors that control the rock fragmentation in opencast bench blasting: A case study conducted over four opencast coal mines of the Talcher Coalfields, India. Journal of Sustainable Mining. 2019;18(4):247–256. https://doi.org/10.1016/j.jsm.2019.08.003
8. Xie C., Nguyen H., Bui X.-N., Choi Y., Zhou J., Nguyen-Trang T. Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms. Geoscience Frontiers. 2020;12(3):101108. https://doi.org/10.1016/j.gsf.2020.11.005
9. Dhekne P.Y., Balakrishnan V., Jade R.K. Effect of type of explosive and blast hole diameter on boulder count in limestone quarry blasting. Geotechnical and Geological Engineering. 2020;38:4091–4097. https://doi.org/10.1007/s10706-020-01280-y
10. Siddiqui F.I., Ali Shah S.M., Behan M.Y. Measurement of size distribution of blasted rock using digital image processing. Journal of King Abdulaziz University-Engineering Sciencess. 2009;20(2):81–93. https://doi.org/10.4197/eng.20-2.4
11. Sudhakar J., Adhikari G.R., Gupta R.N. Comparison of fragmentation measurements by photographic and image analysis techniques. Rock Mechanics and Rock Engineering. 2006;39(2):159–168. https://doi.org/10.1007/s00603-005-0044-9
12. de Souza J.C., da Silva A.C.S., Rocha S.S. Analysis of blasting rocks prediction and rock fragmentation results using splitdesktop software. Technology in Metallurgy, Materials and Mining. 2018;15(1):22–30. https://doi.org/10.4322/2176-1523.1234
13. Tosun A. A modified Wipfrag program for determining muckpile fragmentation. Journal of the Southern African Institute of Mining and Metallurgy. 2018;118(10):1113–1199. https://doi.org/10.17159/2411-9717/2018/v118n10a13
14. Elahi A.T., Hosseini M. Analysis of blasted rocks fragmentation using digital image processing (case study: limestone quarry of Abyek Cement Company). International Journal of Geo-Engineering. 2017;8:16. https://doi.org/10.1186/s40703-017-0053-z
15. Ruszala M.J.A. Fines reduction and energy optimisation in aggregates production [MRes Chemical Engineering Sciences]. The University of Birmingham; May 2013. Available at: https://etheses.bham.ac.uk/id/eprint/4317/1/Ruszala13MRes.pdf (accessed: 12.03.2025).
16. Великанов В.С., Бочков В.С., Дёрина Н.В., Бочкова К.В. Оценка технического состояния футеровочной брони конусных дробилок на основе цифровой диагностики их поверхностей. Горный информационно-аналитический бюллетень. 2022;(11-2):159–168. https://doi.org/10.25018/0236_1493_2022_112_0_159 Velikanov V.S., Bochkov V.S., Dyorina N.V., Bochkova K.V. Digital image processing for assessing the liner armor condition of cone crushers. Mining Informational and Analytical Bulletin. 2022;(11-2):159–168. (In Russ.) https://doi.org/10.25018/0236_1493_2022_112_0_159
17. Дремин А.В., Великанов В.С. Постановка многокритериальной задачи анализа и прогнозирования гранулометрического состава взорванных горных пород. Горная промышленность. 2023;(5):52–60. https://doi.org/10.30686/1609-9192-2023-5-52-60 Dremin A.V., Velikanov V.S. Setting a multi-criteria problem to analyze and forecast particle size distribution of blasted rock. Russian Mining Industry. 2023;(5):52–60. (In Russ.) https://doi.org/10.30686/1609-9192-2023-5-52-60
18. Дремин А.В., Великанов В.С. Цифровые технологии для взрывных работ: интеллектуальный автономный программно-аппаратный комплекс компании «Давтех» для анализа гранулометрического состава горных пород. Горная промышленность. 2023;(6):57–62. https://doi.org/10.30686/1609-9192-2023-6-57-62 Dremin A.V., Velikanov V.S. Digital technologies in blasting: DAVTECH’s intelligent autonomous hardware-andsoftware suite for analyzing particle size distribution of rocks. Russian Mining Industry. 2023;(6):57–62. (In Russ.) https://doi.org/10.30686/1609-9192-2023-6-57-62
19. Великанов В.С., Гришин И.А., Лукашук О.А., Дегодя Е.Ю., Тельминов Н.С. Исследование напряженно-деформированного состояния рабочего органа карьерного экскаватора при динамических нагрузках от грансостава пород. Уголь. 2024;(12):103–107. Velikanov V.S., Grishin I.A., Lukashuk O.A., Degodya E.Yu., Telminov N.S. Study of the stress-strain state of the working body of a quarry excavator under dynamic loads from the granulometric composition of rocks. Ugol’. 2024;(12):103–107. (In Russ.)
20. Великанов В.С., Дремин А.В., Чернухин С.А., Ломовцева Н.В. Технологии нейронных сетей в интеллектуальном анализе данных гранулометрического состава взорванных пород. Горная промышленность. 2024;(4):90–94. https://doi.org/10.30686/1609-9192-2024-4-90-94 Velikanov V.S., Dremin A.V., Chernukhin S.A., Lomovtseva N.V. Neural network technologies in mining data on particle size distribution of muck pile rocks. Russian Mining Industry. 2024;(4):90–94. (In Russ.) https://doi.org/10.30686/1609-9192-2024-4-90-94
21. Великанов В.С., Чернухин С.А., Тельминов Н.С., Дремин А.В., Ломовцева Н.В4, Ситдикова С.В. О влиянии гранулометрии взорванной горной массы на распределение напряжений в рабочем оборудовании карьерного экскаватора. Вестник Магнитогорского государственного технического университета им. Г.И. Носова. 2024;22(4):30–43. Режим доступа: https://vestnik.magtu.ru/novyj-nomer/121-arkhiv-nomerov/4-2024/1657-30.html (дата обращения: 26.02.2025). Velikanov V.S., Chernukhin S.A., Telminov N.S., Dremin A.V., Lomovtseva N.V., Sitdikova S.V. On the influence of the granulometry of blasted rock mass on the stress distribution in the working equipment of a quarry excavator. Vestnik of Nosov Magnitogorsk State Technical University. 2024;22(4):30–43. (In Russ.) Available at: https://vestnik.magtu.ru/novyjnomer/121-arkhiv-nomerov/4-2024/1657-30.html (accessed: 26.02.2025).
