RESEARCH PAPER
Mineralogical Analysis of Iron Ore Using Ultrasonic Wave Propagation Parameters
1
Chair of Measurement and Control Systems, Bayreuth University, Universitätsstraße, 30, Bayreuth, Germany
2
Automation, Computer Science and Technologies Department, Kryvyi Rih National University, Vitalii Matusevich St., 11, Kryvyi Rih, Ukraine
3
Research Department, Kryvyi Rih National University, Vitalii Matusevich St., 11, Kryvyi Rih, Ukraine
Submission date: 2022-09-28
Acceptance date: 2023-03-13
Online publication date: 2023-07-11
Publication date: 2023-09-01
Acta Mechanica et Automatica 2023;17(3):364-371
KEYWORDS
ABSTRACT
Availability, relative simplicity and low cost, combined with ever-increasing capabilities, have led to a significant increase in the use of ultrasonic measurements of mining process variables in recent times. The scope of application varies from the study of the characteristics of raw materials and products of its processing to the operational assessment of the current parameters characterising the state of the process equipment. The purpose of this study is to develop methods for obtaining information about the characteristics of mineral raw materials as a result of ultrasonic logging of wells in a rock mass. The proposed approach makes it possible to improve the quality of information support for the management of technological processes of mining and processing of ore and thereby improve the quality of products supplied to the metallurgical stage and reduce overall production costs.
REFERENCES (40)
1.
Zak A. Global Iron Ore Market to Reach 2.7 Billion Metric Tons by 2026. Global Industry Analysts (Internet). 2022. Available from: https://www.prnewswire.com/new....
2.
Falagán C, Grail BM, Johnson DB. New approaches for extracting and recovering metals from mine tailings, Miner Eng. 2017;106:71–8. 10.1016/j.mineng.2016.10.008.
3.
Golik V, Komashchenko V, Morkun V, Zaalishvili V. Enhancement of lost ore production efficiency by usage of canopies, Metall Mining Ind. 2015;7(4):325–9.
4.
Henckens T. Scarce mineral resources: Extraction, consumption and limits of sustainability. Resour Conserv Recy. 2021;169(105511): 1–12. 10.1016/j.resconrec.2021.105511.
5.
Morkun V, Semerikov S, Hryshchenko S, Slovak K. Environmental geo-information technologies as a tool of pre-service mining engineer’s training for sustainable development of mining industry. CEUR Workshop Proc 1844. 2017;303–10.
6.
El Abassi D, Faiz B, Ibhi A, Aboudaoud I. A new ultrasound method for measuring the physical and mechanical properties of rocks. J Environ Eng Geophys. 2016;21(1):29–36. 10.2113/JEEG21.1.29.
7.
Bhave V, Chimankar OP, Dhoble SJ. Determination of compressive strength of rocks using ultrasound. AIP Conf Proc. 2104 (ICMBAT 2018). 2019;(020035):1–8. 10.1063/1.5100403.
8.
Morkun V, Morkun N, Pikilnyak A. Iron ore flotation process control and optimization using high-energy ultrasound. Metall Mining Ind. 2014;6(2):36–42.
9.
Ishimoto T, Suetoshi R, Cretin D, Hagihara K, Hashimoto J, Kobayashi A, Nakano T. Quantitative ultrasound (QUS) axial transmission method reflects anisotropy in micro-arrangement of apatite crystallites in human long bones: A study with 3-MHz-frequency ultrasound. Bone. 2019;127:82–90. 10.1016/j.bone.2019.05.034.
10.
Oelze ML. Statistics of scatterer property estimates. In: Mamou J, Oelze ML. Quantitative Ultrasound in Soft Tissues. Springer, Dordrecht etc. 2013:43–69.
11.
Morkun V, Morkun N, Tron V. Distributed control of ore beneficiation interrelated processes under parametric uncertainty. Metall Mining Ind. 2015;7(8):18–21.
12.
Zagzebski JA, Rosado-Mendez IM, Nasief HG, Hall TG. Quantitative ultrasound: Enhancing diagnosis using estimates of acoustic attenuation and backscatter. AIP Conf Proc 1747 (Medical Phys). 2016;(050001):1–10. 10.1063/1.4954108.
13.
Dunn MJ. Quantifying uncertainty in mining geomechanics design. Proc First Int Conf Mining Geomech Risk (MGR 2019). 2019;391-402. 10.36487/ACG_rep/1905_23_Dunn.
14.
Golik V, Komashchenko V, Morkun V, Gaponenko I. Improving the effectiveness of explosive breaking on the bade of new methods of borehole charges initiation in quarries. Metall Mining Ind. 2015;7(7):383–7.
15.
Garia S, Pal AK, Ravi K. Elastic wave velocities as indicators of lithology-based geomechanical behaviour of sedimentary rocks: an overview. SN App Sci. 2020;2(1521):1–21. 10.1007/s42452-020-03300-1.
16.
Soroush H, Qutob H. Evaluation of rock properties using ultrasonic pulse technique and correlating static to dynamic elastic constants. Proc 2nd South Asain Geosci Conf Exhibition (GEO India 2011). 2011:1–12. Available from: http://www.mkckorea.com/catalo....
17.
Arsyad M, Tiwow VA, Sulistiawaty, Sahdian IA. Analysis of physical properties and mechanics of rocks in the karst region of Pangkep Regency. J Phys:Conf Ser. 2020;1572(012008):1–8. 10.1088/1742-6596/1572/1/012008.
18.
Morkun V, Morkun N, Tron V. Distributed closed-loop control formation for technological line of iron ore raw materials beneficiation. Metall Mining Ind. 2015;7(7):16–9.
19.
Chawre B. Correlations between ultrasonic pulse wave velocities and rock properties of quartz-mica schist. J Rock Mech Geotech Eng. 2018;10(3):594–602. 10.1016/J.JRMGE.2018. 01.006.
20.
Zuo JP, Wei X, Shi Y, Liu C, Li M, Wong RHC. Experimental study of the ultrasonic and mechanical properties of a naturally fractured limestone. Int J Rock Mech Mining Sci. 2020;125(104162). 10.1016/j.ijrmms.2019.104162.
21.
Bartoszek S, Stankiewicz K, Kost G, Ćwikła G, Dyczko A. Research on ultrasonic transducers to accurately determine distances in a coal mine conditions. Energies. 2021;14(2532). 10.3390/en14092532.
22.
Cerrillo C, Jiménez A, Rufo M, Paniagua J, Pachón FT. New contributions to granite characterization by ultrasonic testing. Ultrasonics. 2014;54(1):156–67. 10.1016/j.ultras.2013.06.006.
23.
Basu A, Aydin A. Evaluation of ultrasonic testing in rock material characterization. Geotech Test J. 2006;29(2):117–25. 10.1520/GTJ12652.
24.
McClements DJ. Ultrasonic Measurements in particle size analysis. In: Meyers, RA. Encyclopedia of Analytical Chemistry. Wiley Online. 2006. 10.1002/9780470027318.a1518.
25.
Samaitis V, Jasiūnienė E, Packo P, Smagulova D. Ultrasonic methods. In: Sause MGR, Jasiūnienė E (eds.). Structural Health Monitoring Damage Detection Systems for Aerospace. Springer Nature, Cham, Switzerland. 2021;87–131. 10.1007/978-3-030-72192-3_5.
26.
Morkun V, Morkun N. Estimation of the crushed ore particles density in the pulp flow based on the dynamic effects of high-energy ultrasound. Arch Acoust. 2018;43(1):61–7. 10.24425/118080.
27.
De Villiers JPR, Lu L. XRD analysis and evaluation of iron ores and sinters. Iron Ore. 2015;85–100. 10.1016/B978-1-78242-156-6.00003-4.
28.
Gerali F. Well Logging, Engineering and Technology History Wiki. 2019. Available from: https://ethw.org/Well_Logging.
29.
Haldar SK. Mineral Exploration: Principles and Applications Elsevier, Amsterdam etc. Second ed. 2018.
30.
Liu CR. Laterolog tools and array laterolog tools. In: Liu CR, Theory of Electromagnetic Well Logging. Elsevier, Amsterdam etc. 2017;579-624.
31.
Khan K, Vantala A, Mohiuddin M. Dependence of ultrasonic velocities and dynamic elastic rock properties on stress and saturation changes. Proc Int Symp Soc Core Analysts. 2005;(SCA2005-64): 1–6.
32.
Kenigsberg AR, Rivière J, Marone C, Saffer DM. A method for determining absolute ultrasonic velocities and elastic properties of experimental shear zones. Int J Rock Mech Mining Sci. 2020;130(104306). 10.1016/j.ijrmms.2020.104306.
33.
Feynman R, Leighton R, Sands M. Sound. The wave equation. In: Lectures in Physics, vol 1, ch 47. Caltech. 2022. Available from: https://www.feynmanlectures.ca....
34.
Acoustic properties of rocks [in Russian]. 2017. Available from: http://ctcmetar.ru/volnovye-pr....
35.
Acoustic velocity logging [in Russian]. 2019. Available from: http://fccland.ru/dobycha-neft....
36.
Lazarenko YK. Mineralogiya Krivorozhskogo basseyna [Mineralogy of the Kryvyi Rih basin; in Russian]. Naukova dumka, Kyiv. 1977.
37.
Koryakov-Savoyskiy BA, Gulenko TI, Lopatin VI. Issledovaniye izmel’chayemosti rud s tsel’yu razrabotki sredstv avtomatizatsii [Study of the grindability of ores in order to develop automation tools; in Russian]. Avtomatizatsiya gornorudnogo i metallurgicheskogo proizvodstva: NIIAchermet, 7.13–20.38. 1971.
38.
Shtovba SD. Vvedeniye v teoriyu nechetkikh mnozhestv i nechetkuyu logiku [Introduction to the theory of fuzzy sets and fuzzy logic; in Russian]. 2014. http://matlab.exponenta.ru/fuz....
39.
Morkun V, Morkun N, Tron V, Hryshchenko S, Serdiuk O, Dotsenko I. Basic regularities of assessing ore pulp parameters in gravity settling of solid phase particles based on ultrasonic measurements. Arch Acoust. 2019;44(1):161–7. 10.24425/aoa.2019.126362.
40.
Azarian A, Azarian V, Morkun V. Operational Quality Control of Ferrous Metal Ores. Lambert Academic Publishing, London, UK. 2022.
| eISSN: | 2300-5319 |
| ISSN: | 1898-4088 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
