ISSN (print) 1995-2732
ISSN (online) 2412-9003

 

download PDF

DOI: 10.18503/1995-2732-2022-20-2-13-22

Abstract

It is well known that a crushing process is one of the most energy intensive technological processes in mineral processing. The aim of this process is to achieve the required size of the processed raw material. The course of the crushing process is characterized by the influence of a number of basic factors: multidimensionality, multiple connections, nonlinearity, physical and mechanical properties of the mineral, shape and size of rock lumps, position of the crushing material inside the crushing chamber, lumps movement speed, wear of a liner and elements of the crusher, as well as design parameters of the crusher. Efficiency of the crushing process in the process flow of solid mineral processing is achieved by applying reasonable operation parameters of crushing equipment, ensuring the set performance and particle size distribution of the crushed ore at minimum electricity consumption. When processing minerals, the size is often monitored between individual operations. Objective. The objective is to provide an innovative solution in developing intelligent systems for automatic control, resulting in adaptive control, depending on changes of the material size distribution by making measurements “inside” the technological equipment. Methods Applied. Methodology of fuzzy logic theory and fuzzy sets was used. Originality. We made it possible to distinguish frame differences in a video stream to detect defects and wear of a crusher liner. Result. The paper identifies an approach to monitoring the discharge slot width for crushing and milling complexes using intelligent control methods.

Keywords

minerals, crusher, control, sensor, fuzzy logic, controller.

For citation

Grishin I.A., Bochkov V.S., Velikanov V.S., Dyorina N.V., Surovtsov M.M., Moreva Yu.A. Implementing a Discharge Slot Width Control System in Cone Crushers.VestnikMagnitogorskogoGosudarstvennogoTekhnicheskogoUniversitetaim.G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University].2022, vol. 20, no. 2, pp. 13–22. https://doi.org/10.18503/1995-2732-2022-20-2-13-22

Grishin I.A. Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia

Bochkov V.S. Ural State Mining University, Yekaterinburg, Russia

Velikanov V.S. Ural State Mining University, Yekaterinburg, Russia, Ural Federal University, Yekaterinburg, Russia

Dyorina N.V. Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia

Surovtsov M.M.Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia

Moreva Yu.A. Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia

1. https://solidground.sandvik/

2. GrishinI.A., IsmagilovK.V., VelikanovV.S. Elektromekhanicheskoeoborudovanierudoobogatitelnykhfabrik: laboratornypraktikum[Electromechanicalequipmentoforeprocessingplants: laboratoryworkshop]. Magnitogorsk: Nosov Magnitogorsk State Technical University, 2015, 68 p. (In Russ.)

3. Klushantsev B.V., Kosarev A.I., Muizemnek Yu.A. Drobilki. Konstruktsiya, raschet, osobennosti ekspluatatsii [Crushers. Design, calculation, operation features]. Moscow: Mechanical engineering, 1990, 320 p.(In Russ.)

4. Marinich I.A., Savitsky A.I. A distributed automatic control system for ore preparation based on industrial controllers. Vestnik IrGTU [Bulletin of Irkutsk State Technical University], 2013, no. 4, pp. 24–29. (In Russ.)

5. Petrovich S.I., Mukusheva A.S., Stukalova N.G. Features of developing and implementing mathematical models to control mining and processing of multicomponent ores. Gorny informatsionno-analiticheskiy byulleten[Mining Informational and Analytical Bulletin], 2002, no. 3, pp. 229–231. (In Russ.)

6. Suetina T.A., Kochetkov A.V., Tolmachev A.G. et al. Features of automatic control of primary crushers. Internet-zhurnal Naukovedenie [Naukovedenie Internet journal], 2015, vol. 7, no. 5, pp.2–11. (In Russ.)

7. Ilyukhin A.V., Kolbasin A.M., Marsov V.I. Matematicheskoe opisanie obektov avtomatizatsii stroitelnogo proizvodstva: uchebnoe posobie [A mathematical description of automation objects of construction: textbook]. Moscow: Moscow Automobile and Road Construction State Technical University(MADI), 2016, 104 p. (In Russ.)

8. Ganbaatar Z., Delgerbat L. Results of the development and implementation of an automated planttechnological control system for the operation of crusher KMD-3000T2- DP. Novye resheniya v tekhnike i tekhnologii dobychi i pererabotki rud: sb. dokl. Mezhdunar. nauch.-prakt. konf. [New solutions in machinery and technology applied for ore mining and processing: collection of the reports presented at the International Scientific and Practical Conference], 3–5 Oct. 2002, Erdenet, pp. 255–29. (In Russ.)

9. Ganbaatar Z., Delgerbat L., Duda A.M. et al. Controlling enrichment of copper-molybdenum ores based on an integrated radiometric analysis of ore.Materialy mezhdunarodnoy konferentsii Plaksinskie chteniya [Proceedings of the international conference Plaksin Readings], Yekaterinburg, 2011, pp. 118–121. (In Russ.)

10. Ganbaatar Z., Zimin A.V., Solovyova L.M. et al. Improving the technology of beneficiation of copper-molybdenum ores at the Erdenet Mining Corporation deposit. Gorny zhurnal [Mining Journal], 2010, no. 10, pp. 34–36. (In Russ.)

11. Morozov I.N., Kirillov I.E. Application of fuzzy logic methods to create an automatic control system for crushing ore of various hardness by coarse crusher KKD- 1500/180. Trudy Kolskogo nauchnogo tsentra RAN [Proceedings of the Kola Scientific Center of the Russian Academy of Sciences], 2017, vol. 8, no. 3–8, pp. 135–143. (In Russ.)

12. Boyko P.F., Titievskiy E.M., Timiryazev V.A. et al. Ensuring the durability of crusher liners by using new technologies for their manufacturing and diagnosing wear. Oborudovanie i tekhnologii dlya neftegazovogo kompleksa[Equipment and technologies for the oil and gas complex], 2019, no. 5 (113), pp. 42–47. (In Russ.)

13. Khurelchuluun I. Povyshenie effektivnosti rudopodgotovki na osnove primeneniya nepreryvnogo viziometricheskogo analiza granulometricheskogo sostava produktov drobleniya i grokhocheniya: dis. kand. tekhn. nauk [Improving the efficiency of ore preparation based on the use of a continuous visual analysis of the granulometric composition of crushing and screening products. PhD thesis]. Moscow, 2019, 127 p.

14. Boyko P.F. Innovatsionnye tekhnologii remonta drobilno-izmelchitelnogo oborudovaniya [Innovative technologies for repairing crushing and grinding equipment]. Stary Oskol: ROSA, 2016, 327 p. (In Russ.)

15. Boiko P.F., Titievskii E.M., Timiryazev V.A. Technological features of operation, repair, restoration and modernization of cone crushers of large unit capacity. Gorny zhurnal [Mining Journal], 2017, no. 4, pp. 71–75. (In Russ.)

16. Khurelchuluun I., Morozov V.V., Nikolaeva T.S., Kruglov V.N. Application of a visual analysis of an ore granulometric composition for automated control of a crushing process. Rudy i metally [Ores and metals], 2019, no. 1, pp. 67–73. (In Russ.)

17. Timiryazev V.A., Khostikoev M.Z., Skhirtladze A.G. et al. Metrologicheskoe obespechenie neftegazovogo mashinostroyeniya [Metrological support of oil and gas machine building]. Moscow: Publishing Center of the Gubkin Russian State University of Oil and Gas (National Research University), 2018, 332 p. (In Russ.)

18. Timiryazev V.A., Novikov V.Yu., Skhirtladze A.G. Tekhnologiya mashinostroeniya[Engineering technology]. Moscow: Publishing House of Moscow State University of Technology STANKIN, 2019, 547 p. (In Russ.)

19. Narkevich M.Yu., Logunova O.S., Kornienko V.D. et al. Quality of materials, products and structures in industrial safety: empirical basis. Vestnik Magnitogorskogo gosudarstvennogo tekhnicheskogo universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University], 2021, vol. 19, no. 3, pp. 90–101. (In Russ.)

20. Velikanov V.S. Development of fuzzy modeling algorithms for intelligent decision support to determine the level of ergonomics of open pit excavators. Gornaya promyshlennost [Mining Industry], 2011, no. 5(99), pp. 64–68. (In Russ.)

21. Shirinkina E.V. The need to adapt human resources (HR) and learning processes to the conditions of uncertainty and turbulence. Vestnik Udmurtskogo universiteta. Seriya: Ekonomika i pravo [Bulletin of Udmurt University. Series: Economics and Law], 2022, vol. 32, no. 1, pp. 102–108. (In Russ.)

22. Velikanov V.S. Using fuzzy logic and fuzzy set theory to control the ergonomic indicators of the quality of mining excavators.Gorny informatsionno-analiticheskiy byulleten[Mining Informational and Analytical Bulletin],2010, no. 9, pp. 57–62. (In Russ.)