Soyuztsvetmetavtomatika JSC, Moscow, Russia:

S. S. Khaymovskiy, Head of the Process Automation Laboratory, e-mail: 34@scma.ru

This paper considers pre-requisite conditions for developing grinding mill control systems and describes the main problems of control and existing constraints. The author selected a set of grinding equipment that consists of autogenous grinding mills and ball mills. The paper considers the selected mill types as control objects. It is shown that there exists a good correlation between the mill charge and its acoustic and vibration noise. The paper examines the relationship between the level of vibroacoustic noise and the mill motor power draw and defines what can be considered an extreme dependence, as well as the conditions in which a stable operation of the automatic system can be maintained excluding the mill overload mode. The paper specifies what hardware and software means would be necessary to implement such system and describes the mill charge analyzer VAZM-1M developed by Soyuztsvetmetavtomatika that was selected for this application. The author looks at certain downsides typical of the conventional control scheme when the head mill feed rate changes as the mill motor power draw changes without allowing for changing physical and mechanical properties of the ore material. The author also considers the capability of the VAZM-1M analyzer in terms of mill load estimation accuracy. This laid the basis for developing mill protection and optimization algorithms for the AG and Ball Mill comminution circuit. The paper features a block diagram of the control algorithm and its brief description. The algorithm consists of blocks, which are responsible for the following actions: they receive key process parameters from the process control system database, check them for validity, perform initial processing and filtering; after that they analyze the trends of the measured parameters and analyze if an overload condition is probable. As decided by the mill operator, the ore flow rate can be adjusted. The paper describes a case study of running an AG mill control system on the basis of the above described algorithm and using the VAZM-1M analyzer. It is noted that this algorithm can be implemented both as an adviser for the operator and for automatic control of the mill when running in overload mode.

1. Shinkorenko S. F. Grinding of ferrous metal ores. Moscow : Nedra, 1982. 212 p.
2. Guerrero F., Bouchard J., Poulin E., Sbarbaro D. Real-time simulation and control of a SAG mill. IFAC-PapersOnLine. 2016. Vol. 49, No. 20. pp. 61–66.
3. Ulitenko K. Ya., Popov E. V. Automatic protection of tumbling mills from overload. Obogashchenie Rud. 2004. No. 2. pp. 38-39.
4. Pourghahramani P. Effects of ore characteristics on product shape properties and breakage mechanisms in industrial SAG mills. Minerals Engineering. 2012. Vol. 32. pp. 30–37.
5. Shchupanovskiy V. F., Malyavin B. Ya., Popov V. P. et al. A control system for the process of autogenous ore grinding. Gornyi Zhurnal. 1996. No. 3. Р. 31.
6. Ulitenko K. Ya., Sokolov I. V., Ma rkin R. P. Noise and vibration analysis used to control volumetric mill charge. Tsvetnye Metally. 2005. No. 10. pp. 63-66.
7. Pivnyak G. G., Vaysberg L. A., Kirichenko V. I. et al. Comminution. Power engineering and technology. Moscow : “Ore and Metals” Publishing House, 2007. 296 p.
8. Temkin I. O., Myaskov A. V., Deryabin S. A., Rzazade U. A. Digital twins and modeling of the transporting-technological processes for on-line dispatch control in open pit mining. Eurasian Mining. 2020. No. 2. pp. 55–58.
9. VAZM-1M: Vibroacoustic mill charge analyzer. Available at: http://www.scma.ru/ru/products/2-444.html
10. Damba-Ochir D., Kimyaev I. T., Ulitenko K. Ya. Designing a grinding mill control system with the vibroacoustic mill charge analyzer VAZM-1M. Tsvetnye Metally. 2003. No. 10. pp. 112–115.
11. Silva M., Casali A. Modelling SAG milling power and specific energy consumption including the feed percentage of intermediate size particles. Minerals Engineering. 2015. Vol. 70. pp. 156–161.
12. Ulitenko K. Ya., Markin R. P. Grinding mill circulating load determined with the help of process control systems. Obogashchenie Rud. 2005. No. 2. pp. 42–46.
13. Braverman E. M. Extreme parameter grouping and the problem of identifying essential factors. Avtomatika i Telemekhanika. 1970. No. 1. pp. 123–132.
14. Anderson T. The Statistical Analysis of Time Series. Moscow : Mir, 1976. 756 p.
15. Borisov A. N. et al. Fuzzy information processed by decision-making systems. Moscow : Radio i svyaz, 1989. 302 p.
16. Soda R., Sato A., Kano J., Saito F. Development of prediction method of wear rate during wet stirred milling by using DEM. Journal of the Society of Powder Technology. 2014. Vol. 51, No. 6. pp. 436–443.
17. Asai K. et al. Applied fuzzy systems. Moscow : Mir, 1993. 368 p.
18. Pospelov D. A. Situational control. Moscow : Nauka, 1986. 288 p.
19. Melikhov A. N., Bershtein L. S., Korovin S. Ya. Situational advisory systems with fuzzy logic. Moscow : Nauka, 1990. 271 p.
20. Rykov A. S. Systems analysis methods: Optimization. Moscow : Ekonomika, 1999.