Neural network model of the mechatron complex “crusher mill”

• Autorzy: Kalinchyk Vasyl , Meita Olexandr , Pobigaylo Vitalii , Kalinchyk Vitalii , Filyanin Danylo

Identyfikatory

DOI

10.53412/jntes-2021-2.4

• Języki publikacji: EN

Abstrakty

EN

The paper discusses the use of the technology of artificial neural networks to improve technical and economic performance of crushing and milling complex. Formulated the goal and major tasks of constructing a system of automated control and monitoring to optimize the power consumption of crushing and milling complex is analyzed modes of complex mechatronic and development of multicriteria models to provide optimal technological parameters of the equipment.

Słowa kluczowe

EN

crushing and grinding complex; modelling; neural network

• Wydawca: Kielce University of Technology
• Czasopismo: Journal of New Technologies in Environmental Science
• Rocznik: 2021
• Tom: Vol. 5, nr 2
• Strony: 72--81
• Opis fizyczny: Bibliogr. 8 poz., rys., tab., wykr., wzory

Twórcy

autor

Kalinchyk Vasyl

• National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine

autor

Meita Olexandr

• National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine

autor

Pobigaylo Vitalii

• National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine

autor

Kalinchyk Vitalii

• National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine

autor

Filyanin Danylo

• National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine

Bibliografia

• [1] Meyta A.V., Monitoring and control system of crushing and grinding complex, Dis. ... Cand. tech. Sciences: 05.09.03 Kiev, 2010.
• [2] Kyrychenko V., Concerning CAE development of hydraulic hoists within ship mining complexes, Kyrychenko V., Kyrychenko E., Samusya V., Antonenko A., Annual collection of scientific-technical papers “Progressive Technologies of Coal, Coalbed Methane, and Ores mining”, Taylor & Francis group, London, UK, 2014, pp. 451-456.
• [3] Samusya V., The choice of rational parameters of the heat pump installation for the utilization of low-potential heat of mine water, Samusya V., Oksen Y., Huk O., Metallurgical and mining industry, Science and Technology and production magazine, 2015, vol. 1 (92), pp. 126-131.
• [4] Pivniak G., Parameters optimization of heat pumps units in mining enterprises, Pivniak G., Samusya V., Oksen Y., Radiuk M., Annual collection of scientific-technical papers “Progressive Technologies of Coal, Coalbed Methane, and Ores mining”: Taylor & Francis group, London, UK, 2014, pp. 19-24.
• [5] Meyta A.V., Investigation of the Factor Field of a Ball Mill, Meyta A.V. Energy: Economics, Technology, Ecology, 2016, No. 1, pp. 96-101.
• [6] Rosen V., Optimization of power consumption of the grinding and grinding complex, Rosen V., Kalinchik V., Meyta A., Skosirev V., Energy: Economics, Technology, Ecology, 2015, No. 1, pp. 43-47.
• [7] Callan R., Neural networks, Per. from English, M.: Hot line - Telecom, 2000, 280 p.
• [8] Medvedev V.S., Neural networks. MATLAB 6, Textbook, Medvedev V.S. under. total ed. Potemkin V.G., M.: DIALOGUE-MIFI, 2002, 496 p.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).