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All issues Volume 201 (2020) E3S Web Conf., 201 (2020) 01025 References
Open Access
Issue
E3S Web Conf.
Volume 201, 2020
Ukrainian School of Mining Engineering - 2020
Article Number 01025
Number of page(s) 9
DOI https://doi.org/10.1051/e3sconf/202020101025
Published online 23 October 2020
  1. Azarian, V.A. (2019). Tekhnoloho-teoretychni zasady upravlinnia iakistiu zalizovmisnoi syrovyny heneralizovanoho kompleksu rudopotokiv hirnycho-zbahachuvalnykh kombinativ. PhD Thesis. Kryvyi Rih, Ukraine: KNU. [Google Scholar]
  2. Stupnik, M.I., Kalinichenko, V.O., Pysmennyi, S.V., & Kalinichenko, O.V. (2018). Determining the qualitative composition of the equivalent material for simulation of Kryvyi Rih iron ore basin rocks. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (4), 21-27.https://doi.org/10.29202/nvngu/2018-474 [CrossRef] [Google Scholar]
  3. Kupin, A., Kuznetsov, D., Muzyka, I., Paraniuk, D., Serdiuk, O., Suvorov, O., & Dvornikov, V. (2018). The concept of a modular cyberphysical system for the early diagnosis of energy equipment. Eastern-European Journal of Enterprise Technologies, 4(2(94)), 71-79.https://doi.org/10.15587/1729-4061.2018.139644 [CrossRef] [Google Scholar]
  4. Morkun, V., Semerikov, S., Hryshchenko, S., & Slovak, K. (2017). Environmental geoinformation technologies as a tool of pre-service mining engineer’s training for sustainable development of mining industry. CEUR Workshop Proceedings, (1844), 303-310. [Google Scholar]
  5. Kalinichenko, V., Pysmennyi, S., Shvaher, N., & Kalinichenko, O. (2018). Selective underground mining of complex structured ore bodies of Kryvyi Rih Iron Ore Basin. E3S Web of Conferences, (60), 00041. https://doi.org/10.1051/e3sconf/20186000041 [CrossRef] [EDP Sciences] [Google Scholar]
  6. Morkun, V., & Tron, V. (2014). Automation of iron ore raw materials beneficiation with the operational recognition of its varieties in process streams. Metallurgical and Mining Industry, (6), 4-7. [Google Scholar]
  7. Abdyldaev, K.K., Kuvakov, S.Z., & Kurmanbek, U.T. (2017). Issledovanie fiziko- mekhanicheskikh svoystv na razlichnykh glubinakh i anizatropii gornykh porod mestorozhdeniya Makmal. Gornaya Promyshlennost, 7(131),93-94. [Google Scholar]
  8. Morkun, V., & Tcvirkun, S. (2014). Investigation of methods of fuzzy clustering for determining ore types, Metallurgical and Mining Industry, (5), 11-14. [Google Scholar]
  9. Morkun, V., Tron, V., & Goncharov, S. (2015). Automation of the ore varieties recognition process in the technological process streams based on the dynamic effects of high-energy ultrasound. Metallurgical and Mining Industry, (2), 31-34. [Google Scholar]
  10. Golik, V., Komashchenko, V., Morkun, V., & Irina, G. (2015). Improving the effectiveness of explosive breaking on the bade of new methods of borehole charges initiation in quarries. Metallurgical and Mining Industry, 7(7),383-387. [Google Scholar]
  11. Golik, V., Komashchenko, V., & Morkun, V. (2015). Feasibility of using the mill tailings for preparation of self-hardening mixtures. Metallurgical and Mining Industry, (3), 38-41. [Google Scholar]
  12. Golik, V., Komashchenko, V., Morkun, V., & Burdzieva, O. (2015). Metal deposits combined development experience. Metallurgical and Mining Industry, (6), 591-594. [Google Scholar]
  13. Golik V., Komashchenko V., Morkun V., & Zaalishvili V. (2015). Enhancement of lost ore production efficiency by usage of canopies. Metallurgical and Mining Industry, (4), 325-329. [Google Scholar]
  14. Morkun, V., Morkun, N., & Tron, V. (2015). Identification of control systems for ore-processing industry aggregates based on nonparametric kernel estimators. Metallurgical and Mining Industry, (1), 14-17. [Google Scholar]
  15. Bublikov, A., & Tkachov, V. (2019). Automation of the control process of the mining machines based on fuzzy logic. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (3), 112-118. https://doi.org/10.29202/nvngu/2019-3/19 [Google Scholar]
  16. Morkun, V., & Tron, V. (2014). Ecological and economic optimization of iron ore processing automated control. Metallurgical and Mining Industry, (5), 8-10. [Google Scholar]
  17. Morkun, V., Morkun, N., & Pikilnyak, A. (2015). Adaptive control system of ore beneficiation process based on Kaczmarz projection algorithm. Metallurgical and Mining Industry, (2), 35-38. [Google Scholar]
  18. Morkun, V., Morkun, N., & Tron, V. (2015). Formalization and frequency analysis of robust control of ore beneficiation technological processes under parametric uncertainty. Metallurgical and Mining Industry, (5), 7-11. [Google Scholar]
  19. Yue, Z.Q., Lee, C.F., Law, K.T., & Lam, L.G. (2015). Automatic monitoring of rotary percussive drilling for ground characterization. International Journal of Rock Mechanics & Mining Sciences, 41(4),573-612. https://doi.org/10.1016/i.iirmms.2003.12.151 [CrossRef] [Google Scholar]
  20. Schunnesson, H. (2014). Rock characterisation using percussive drilling. International Journal of Rock Mechanics & Mining Sciences, 35(6). 711-725. https://doi.org/10.1016/s0148-9062(97)00332-x [CrossRef] [Google Scholar]
  21. Schunnesson, H., & Holme, K. (2015). Drill monitoring for geological mine planning in the Viscaria copper mine, Sweden. CIMBulletin, 90(1030),82-89. [Google Scholar]
  22. Beattie, N. (2012). Monitoring-while-drilling for open-pit mining in a hard rock environment. PhD Thesis. Ontario, Canada: Queen’s University Kingston. [Google Scholar]
  23. Martin, J. (2013). Application of pattern recognition techniques to monitoring-while-drilling on a rotary electric blast hole drill at an open-pit coal mine. PhD Thesis. Ontario, Canada: Queen’s University Kingston. [Google Scholar]
  24. Karotazh skvazhiny. Retrieved from https://neftegaz.ru/tech-library/geologorazvedka-i-geologorazvedochnoe-oborudovanie/147534-karotazh-skvazhiny/ [Google Scholar]
  25. Akusticheskie svoystva gornykh porod. Retrieved from http://ctcmetar.ru/volnovye- processv/9297-akusticheskie-svovstva-gomvh-porod.html [Google Scholar]
  26. Akusticheskiy karotazh po skorosti. Retrieved from http://fccland.ru/dobycha-nefti/6826-akusticheskiy-karotazh-po-skorosti.html [Google Scholar]
  27. Morkun, V., Morkun, N., & Pikilnyak, A. (2(15). The study of volume ultrasonic waves propagation in the gas-containing iron ore pulp. Ultrasonics, (56), 340-343.https://doi.org/10.1016/j.ultras.2014.08.022 [Google Scholar]
  28. Morkun, V., Morkun, N., & Pikilnyak, A. (2014). Ultrasonic facilities for the ground materials characteristics control. Metallurgical and Mining Industry, (2), 31-35. [Google Scholar]
  29. Morkun, V., Morkun, N., & Pikilnyak, A. (2014). Simulation of high-energy ultrasound propagation in heterogeneous medium using k-space method. Metallurgical and Mining Industry, (3), 23-27. [Google Scholar]
  30. Azaryan, A., Gritsenko, A., Trachuk, A., Serebrenikov, V., & Shvets, D. (2019). Using the intensity of absorbed gamma radiation to control the content of iron in ore. Eastern-European Journal of Enterprise Technologies, 3(5(99)), 29-35. https://doi.org/10.15587/1729- 4061.2019.170341 [CrossRef] [Google Scholar]
  31. Azaryan, A., Gritsenko, A., Trachuk, A., & Shvets, D. (2018). Development of the method to operatively control quality of iron ore raw materials at open and underground extraction. Eastern- European Journal of Enterprise Technologies, 5(5(95)). 13-19. https://doi.org/10.15587/1729- 4061.2018.144003 [CrossRef] [Google Scholar]
  32. Azaryan, A.A., Batareyev, A.S., Karamanits, F I., Kolosov, V.A., & Morkun, V.S. (2018). Ways to reduce ore losses and dilution in iron ore underground mining in Kryvbass. Science and Innovation, 14(4), 17-24. https://doi.org/10.15407/scine14.03.017. [CrossRef] [Google Scholar]
  33. Morkun, V., Morkun, N., & Pikilnyak, A. (2014). Ultrasonic phased array parameters determination for the gas bubble size distribution control formation in the iron ore flotation. Metallurgical and Mining Industry, (3), 28-31. [Google Scholar]
  34. Morkun, V., Morkun, N., & Pikilnyak, A. (2014). Simulation of the Lamb waves propagation on the plate which contacts with gas containing iron ore pulp in Waveform Revealer toolbox. Metallurgical and Mining Industry, (5), 16-19. [Google Scholar]
  35. Morkun, V., Morkun, N., & Pikilnyak, A. (2014). The gas bubble size distribution control formation in the flotation process. Metallurgical and Mining Industry, (4), 42-45. [Google Scholar]
  36. Brazhnikov, N.I. (1965). Vl’trazvukovye metody. Moskva-Leningrad: Energiya. [Google Scholar]
  37. Xie, Y., Rodriguez, S., Zhang, W., Liu, Z., & Yin, W. (2016). Simulation of an electromagnetic acoustic transducer array by using analytical method and FDTD. Journal of Sensor, 2016, 1-10. https://doi.org/10.1155/2016/5451821 [Google Scholar]
  38. Romanyuk, M.I. (2015). Teoreticheskie osnovy rascheta ul’trazvukovykh traktov ustroystv kontrolyapoverkhnosti metalloprokata. PhD Thesis. Kyiv, Ukraine: KPI. [Google Scholar]
  39. Kozin, V.Z. (2008). Issledovanie rud na obogatimost’. Ekaterinburg: Ural’skiy gosudarstvennyy gornyy universitet. [Google Scholar]

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