4.4 Article

Methodology for applying control theory in modeling the processes of centrifugal enrichment of mineral raw materials

期刊

SEPARATION SCIENCE AND TECHNOLOGY
卷 58, 期 1, 页码 141-148

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/01496395.2022.2101005

关键词

Gravity beneficiation; gold centrifugal concentration; knelson concentrator; control theory; transfer function; differential equations

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This article presents an approach to applying automatic control theory in the mineral raw materials enrichment process. By representing the process of centrifugal concentration as a transfer function and finding its parameters, the article proposes a modeling method for centrifugal concentrators. The proposed mechanism for determining the transfer function parameters and their calculation based on experimental data was validated using MatLAB software and the Simulink package, resulting in satisfactory results.
The article discusses an approach aimed at the formation of a methodology for applying the principles and models used in the automatic control theory in relation to the processes of enrichment of mineral raw materials. The problem solved in the article is posed as follows, try to represent the process of gravitational enrichment, namely centrifugal concentration, in the form of a transfer function and try to find its parameters. The paper proposes an approach to modeling centrifugal concentrators based on transfer functions, using averaged values of output characteristics. Proposal of a mechanism for determining the parameters of transfer functions and their calculation based on experimental data. To check the presented calculations, the MatLAB software tool with the Simulink package was used. As a result, the transfer function of the KC-CVD6 apparatus used in the gold deposit was found and satisfactory results were obtained. The work uses methods of identification of automatic systems, methods of system analysis, as well as methods of mathematical modeling, namely the numerical solution of differential equations, implemented in the MatLAB environment with the Simulink package. A comparison with the classical regression model was made; as a result, the modeling error was reduced by two times. The simulation error for the concentrate yield was less than 1%.

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