Automatization of control processes at the first stage of ore enrichment using quickly acting regressive models

Khotskina, V. B.

Purpose. Development of high-speed multi-regression models for the operational management of the first stage of ore enrichment. Methodology. Multifactor regression models of controlling of the first stage of grinding - classification - magnetic separation were obtained on statistical material which had been obtained in the result of passive experiment of the first stage of ore enrichment. Methodology of the research of the models of grinding mills charging optimization has been worked out taking into account the composition of complex ores and evaluation of the mass fraction of 0,056 mm class in industrial product classification. Findings. The developed software allows us to build the model of the first stage ore enrichment and control boundary limits of input factors by projecting inception of the problem situation, correcting the models of grinding mills (ball mills) charging and classifying the process of the first stage of ore enrichment. Originality. We have established cause-effect relationships of technological variables of enrichment facilities depending on physical and mechanical properties of ores. Dependence of process parameters on the properties of ore determined by the "production rules" input and output matrices of Petri nets. The main purpose of Petri nets is to identify problematic situations and create "production rules" which form the set of recommendations for the effective operation of the system based on the cause-effect relationships. Practical value. The research resulted into the control system, database and software for automation of ore treatment. The methods of development of management decisions in robot and adaptive control systems of the first stage of enrichment were implemented. The practical recommendations for the effective management of the first stage of ore enrichment based on our algorithms and software have been developed.


	Наукова періодика України		Naukovyi visnyk Natsionalnoho Hirnychoho Universytetu