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

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Category: Information technologies, systems analysis and administration

Last Updated on 10 July 2014

Published on 10 July 2014

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Authors:

V.B. Khotskina, Cand.Sci. (Tech.), Associate Professor, State Higher Educational Institution “National University of Krivoy Rig”, Associate Professor of the Department of Computer Science and Applied Software, Krivoy Rog, Ukraine

Abstract:

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.

References:

1. Babets, Ye.K. (2011), “Technical-economic indicators of mining enterprises of Ukraine for 2009-2010”, GP “NIHRI”, Krivoy Rog, Ukraine.

Технико-экономические показатели горнодобывающих предприятий Украины в 2009–2010 гг. : сб. науч. трудов / под. ред. Е. К. Бабца. - Кривой Рог: ГП „НИГРИ“, 2011. - 309 с.

2. Khorolskiy, V.P., Hotskina, V.B., Khorolska, T.V. and Babets, Ye.K. (2008), Intehrovane intelektualne upravlinnia tekhnolohichnymy protsessamy v ekonomichnykh systemakh korporatyvnykh pidpryemstv hirnycho-metalurhiinoho kompleksu Ukrainy [Integrated Intelligent Control of Technological Processes in Economic Systems of Corporate Mining and Metallurgic Complex], monograph, Sich, Dnepropetrovsk, Ukraine.

Інтегроване інтелектуальне управління технологічними процесами в економічних системах корпоративних підприємств гірничо-металургійного комплексу : монографія / [В.П. Хорольський, В.Б. Хоцкіна, Т.В. Хорольская, Е.К. Бабец ; під. ред. В.П. Хорольського]. – Дніпропетровськ : Січ, 2008. – 443 с.

3. Kochura, Ye.V. (1996), “Development of scientific bases of automation processes magnetic ore enrichment for energy saving”, Abstract of Dr. Sci. (Tech.) dissertation, Dnepropetrovsk, Ukraine.

Кочура Е.В. Развитие научных основ автоматизации процессов магнитного обогащения руд с целью энергосбережения : автореферат дис. на соиск. научн. степени докт. техн. наук / Е.В. Кочура. – Днепропетровск, 1996. – 41 с.

4. Kupin, A.I. (2008), Intellektualna identyficatsiia ta keruvannia v umovakh protsessiv zbahachuvalnoi tekhnolohii [Intelligent Identification and Control of Process in Concentration Technologies], KTU, Kryvyi Rih, Ukraine.

Купін А.І. Інтелектуальна ідентифікація та керування в умовах процесів збагачувальної технології / Купін А.І. – Кривий Ріг : Видавництво КТУ, 2008. – 204 с.

5. Kornienko, V.I. (2009), “Hierarchical adaptive control of ore-preparation processes by the synergistic principle with intelligent forecasting”, Scientific Bulletin of National Mining University, no. 11, pp. 61-66.

Корнієнко В.І. Ієрархічне адаптивне керування процесами рудопідготовки за синергетичним принципом з інтелектуальним прогнозуванням / В.І. Корнієнко // Науковий вісник Національного гірничного університету. – 2009. – № 11. – С. 61-66

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