EFFICIENCY IMPROVEMENT METHOD OF THE IRON ORE PELLETS PRODUCTION PROCESS CONTROL (21-26)

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Дата публикации статьи в журнале: 2020/07/17
Название журнала: Восточно Европейский Научный Журнал, Выпуск: 58, Том: 2, Страницы в выпуске: 21-26
Автор: Oksanich I. G
Kremenchug, Department of Automated and Information Systems,Kremenchug Mikhailo Ostrohradskyi National University , PhD (technical science), associate professor,
Автор: Kovtun D.V
Kremenchug, Kremenchug Mikhailo Ostrohradskyi National University , postgraduate
Анотация: The article describes the method of deepening the monitoring of the firing process of iron ore pellets, in particular, reducing the error of firing temperature measurement inside the rotary kiln. A mathematical model has been developed that describes the composition of the atmosphere inside the kiln and the significant factors that influence the temperature measurement error of a radiation pyrometer. The proposed model was checked for adequacy and the results obtained in the form of calculated values of temperature, standard error for each model value, 95% confidence interval of model values, and 95% confidence interval for average response. The proposed method will increase the efficiency of process control of the iron ore pellets production.
Ключевые слова: monitoring   process control   pellets   firing  
Данные для цитирования: Oksanich I. G , Kovtun D.V , . EFFICIENCY IMPROVEMENT METHOD OF THE IRON ORE PELLETS PRODUCTION PROCESS CONTROL (21-26). Восточно Европейский Научный Журнал. Технические науки. 2020/07/17; 58(2):21-26.

Список литературы: 1.J. G. Krishna, С Rudrappa, B. P. Ravi, M V. Rudramuniyappa Optimization of an Iron Ore Washing Plant. Proccdia Earlh and Planclary Science. 2015. Vol. 11. P. 111-114 2.Gustafsson G., Haggblad H.A. Experimental characterization of constitutive data of iron ore pellets. Powder Technology. 2009. Vol. 194. P. 67-74.. 3.Egorova E.G., Rusinov L.A., Usachev M.A., Analiz protsessa podgotovki aglo-merata iz rud tsvetnykh i chernykh metallov kak ob"ekta avtomaticheskoi dia-gnostiki. Tsvetnye metally. 2013. Vol. 11, P. 87-91. 4.Xiao-hui, F. Real-time operation guide system for sintering process with artificial intelligence / F. Xiao-hui, C. Xu-ling, J. Tao // Journal of central south university of technology, China. – 2005. - Issue 5, Vol. 12 - P. 531-535. 5.Xiang, J. Intelligent Integrated Optimization Control Design of Comprehensive Production Indices for Sintering Process / J. Xiang, M. Wu // Control Conference, China, 2007.- P. 750-754. 6.G. Yang, X. Fan. X. Chen, X. Huang, X. Li. Optimization of Cooling Process of Iron Ore Pellets Based on Mathematical Model and Data Mining. Journal of iron and steel research, international. 2015. Vol. 22 № 11. P. 1002-1008 7.Lisienko V.G. Mathematical Modeling of Energy-Technological Units and Control Models in Energy Saving. Scientific and Technological Achievements Related to the Development of European Cities. Vol. 9. 1996. P. 235–248. 8.Gorbachev V.A. Formirovanie granulometricheskogo sostava okatyshei na fabrikakh okomkovaniya. Gornyi zhurnal. 2003. Vol. 4, №–5. P. 89–91.