Тип публикации: статья из журнала

Год издания: 2021

Идентификатор DOI: 10.5937/jaes0-28489

Ключевые слова: automated control system, fuzzy controller, induction brazing, intellectual system, neural networks, neuro-fuzzy controller, waveguide paths

Аннотация: The article presents the development of a method for selecting the operating mode of the induction brazing process based on intelligent methods. The use of intelligent methods is due to the presence of uncertain conditions caused by the complexity of the initial setting of the technological parameters of the induction brazing proceПоказать полностьюss, the error of measuring instruments, and the human factor. The use of smart methods will make it possible to reduce the impact of negative factors, remove uncertainty, and adequately perform the initial set of technological parameters for the induction brazing process. Artificial neural networks, the fuzzy controller and the neural fuzzy controller have been chosen as the smart methods in this work. The article gives a brief overview of the above methods, provides a rationale for the choice of intelligent methods, and also compares their effectiveness. Based on the results of the experimental efficiency check, the most suitable method for determining the choice of induction brazing process operation is proposed. © 2021 Institut za Istrazivanja. All rights reserved.

Журнал: Journal of Applied Engineering Science

Выпуск журнала: Vol. 19, Is. 2

Номера страниц: 424-431

ISSN журнала: 14514117

Издатель: Institut za Istrazivanja

• Tynchenko V. (Information-Control Systems Department, Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation, Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, Krasnoyarsk, Russian Federation)
• Anton M. (Information-Control Systems Department, Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation)
• Kukartsev V. (Department of Information Economic Systems, Engineering and Economics Institute, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation, Department of Computer Science, Institute of Space and Information Technologies, Siberian Federal University, Krasnoyarsk, Russian Federation)
• Tynchenko V. (Department of Computer Science, Institute of Space and Information Technologies, Siberian Federal University, Krasnoyarsk, Russian Federation, Department of Computer Science and Computer Engineering, Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation)
• Bukhtoyarov V. (Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, Krasnoyarsk, Russian Federation, Department of Information Technology Security, Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation)
• Bashmur K. (Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, Krasnoyarsk, Russian Federation)

• Scopus
• Ядро РИНЦ (eLIBRARY.RU)