Algorithm for non-parametric modeling of the cutting process of dense snow formations with snow plow blade

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific Conference on Applied Physics, Information Technologies and Engineering 2019, APITECH 2019

Год издания: 2019

Идентификатор DOI: 10.1088/1742-6596/1399/4/044051

Аннотация: The paper presents an algorithm for non-parametric modeling of the process of cutting dense snow formations with snow plow blade. The following parameters are used as parameters involved in the model: cutting force components, width, cutting angles and installation of snow plow blade, depth of cut and physicomechanical properties oПоказать полностьюf dense snow formations (density from 400 to 500 kg/m3). The initial data for the construction of the model were the results of experiments conducted on a laboratory model of snow plow blade for snow removal equipment. Optimization of the non-parametric regression model was carried out using evolutionary strategies, and the result was improved by local descent methods. The model is necessary to predict the course of the cutting process in a wide range of changes in the parameters in the process of studying and using it on full-scale real snow removal equipment. © Published under licence by IOP Publishing Ltd.

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Издание

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 1399, Is. 4

Номера страниц: 44051

ISSN журнала: 17426588

Издатель: Institute of Physics Publishing

Авторы

  • Lysyannikov A.V. (Siberian Federal University, Institute of Petroleum and Natural Gas, 82/6, Svobodny Avenu, Krasnoyarsk, 660041, Russian Federation)
  • Agafonov E.D. (Siberian Federal University, Institute of Petroleum and Natural Gas, 82/6, Svobodny Avenu, Krasnoyarsk, 660041, Russian Federation)
  • Egorov A.V. (Volga State University of Technology, Yoshkar-Ola, 3, Lenin Square, 424000, Russian Federation)
  • Lysyannikova N.N. (Siberian Federal University, Institute of Petroleum and Natural Gas, 82/6, Svobodny Avenu, Krasnoyarsk, 660041, Russian Federation)
  • Shram V.G. (Siberian Federal University, Institute of Petroleum and Natural Gas, 82/6, Svobodny Avenu, Krasnoyarsk, 660041, Russian Federation)
  • Kovaleva M.A. (Siberian Federal University, Institute of Petroleum and Natural Gas, 82/6, Svobodny Avenu, Krasnoyarsk, 660041, Russian Federation)

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