MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK
Background. This article presents the composition and algorithm of the automated control system for the parameters of a pneumatic arch-breaking system installed on bunkers with bulk materials. The relevance and practical significance of the issue considered in the article is determined by the fact t...
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| Format: | Article |
| Language: | English |
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Science and Innovation Center Publishing House
2023-03-01
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| Series: | International Journal of Advanced Studies |
| Subjects: | |
| Online Access: | http://ijournal-as.com/jour/index.php/ijas/article/view/177 |
| _version_ | 1797808492071878656 |
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| author | Alexander A. Vorobyov Alexander A. Migrov Irina Yu. Romanova Stanislav S. Evtyukov Oleg V. Moskvichev |
| author_facet | Alexander A. Vorobyov Alexander A. Migrov Irina Yu. Romanova Stanislav S. Evtyukov Oleg V. Moskvichev |
| author_sort | Alexander A. Vorobyov |
| collection | DOAJ |
| description | Background. This article presents the composition and algorithm of the automated control system for the parameters of a pneumatic arch-breaking system installed on bunkers with bulk materials. The relevance and practical significance of the issue considered in the article is determined by the fact that when unloading bulk material from the hopper, various violations of the technological process may occur, manifested in the formation of material freezes inside the container, a decrease in the amount of unloaded material, segregation, up to a complete stop of unloading due to the formation of arches.
Materials and/or methods. Methods of mathematical modeling, system analysis, comparison, systems theory, as well as architecture and mathematical model of a recurrent neural network with feedback are used.
Results. The composition of input and output parameters of the control system is substantiated. Methods for solving problems of classifying parameter sets are considered and an artificial recurrent neural network with feedback and with a sigmoidal activation function of neurons of the hidden layer and a linear activation function of the output layer is selected.
Conclusion. The article analyzes the requirements for the system of automated control of the parameters of the pneumatic arch-breaking system. Based on the analysis of possible states of the system, the composition of the system elements and the sets of input, intermediate and output parameters of the system, as well as the objective function of the system operation, are substantiated. It is shown that the system can be built on the basis of an artificial neural network. The algorithm of the automated control system for the parameters of the pneumatic arch-breaking system has been developed. |
| first_indexed | 2024-03-13T06:38:19Z |
| format | Article |
| id | doaj.art-a0305940c1944a50ae9f872d3ea33715 |
| institution | Directory Open Access Journal |
| issn | 2328-1391 2227-930X |
| language | English |
| last_indexed | 2024-03-13T06:38:19Z |
| publishDate | 2023-03-01 |
| publisher | Science and Innovation Center Publishing House |
| record_format | Article |
| series | International Journal of Advanced Studies |
| spelling | doaj.art-a0305940c1944a50ae9f872d3ea337152023-06-09T04:21:32ZengScience and Innovation Center Publishing HouseInternational Journal of Advanced Studies2328-13912227-930X2023-03-0113122925110.12731/2227-930X-2023-13-1-229-251177MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORKAlexander A. Vorobyov0Alexander A. Migrov1Irina Yu. Romanova2Stanislav S. Evtyukov3Oleg V. Moskvichev4Emperor Alexander I St. Petersburg State Transport UniversityEmperor Alexander I St. Petersburg State Transport UniversityEmperor Alexander I St. Petersburg State Transport UniversityEmperor Alexander I St. Petersburg State Transport UniversitySamara State University of RailwaysBackground. This article presents the composition and algorithm of the automated control system for the parameters of a pneumatic arch-breaking system installed on bunkers with bulk materials. The relevance and practical significance of the issue considered in the article is determined by the fact that when unloading bulk material from the hopper, various violations of the technological process may occur, manifested in the formation of material freezes inside the container, a decrease in the amount of unloaded material, segregation, up to a complete stop of unloading due to the formation of arches. Materials and/or methods. Methods of mathematical modeling, system analysis, comparison, systems theory, as well as architecture and mathematical model of a recurrent neural network with feedback are used. Results. The composition of input and output parameters of the control system is substantiated. Methods for solving problems of classifying parameter sets are considered and an artificial recurrent neural network with feedback and with a sigmoidal activation function of neurons of the hidden layer and a linear activation function of the output layer is selected. Conclusion. The article analyzes the requirements for the system of automated control of the parameters of the pneumatic arch-breaking system. Based on the analysis of possible states of the system, the composition of the system elements and the sets of input, intermediate and output parameters of the system, as well as the objective function of the system operation, are substantiated. It is shown that the system can be built on the basis of an artificial neural network. The algorithm of the automated control system for the parameters of the pneumatic arch-breaking system has been developed.http://ijournal-as.com/jour/index.php/ijas/article/view/177bunkerbulk materialspneumatic vault-breaking systemvault formationautomatic control systemartificial neural networkneural network training |
| spellingShingle | Alexander A. Vorobyov Alexander A. Migrov Irina Yu. Romanova Stanislav S. Evtyukov Oleg V. Moskvichev MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK International Journal of Advanced Studies bunker bulk materials pneumatic vault-breaking system vault formation automatic control system artificial neural network neural network training |
| title | MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK |
| title_full | MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK |
| title_fullStr | MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK |
| title_full_unstemmed | MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK |
| title_short | MANAGEMENT OF THE VAULTING SYSTEM BULK MATERIALS BASED ON A NEURAL NETWORK |
| title_sort | management of the vaulting system bulk materials based on a neural network |
| topic | bunker bulk materials pneumatic vault-breaking system vault formation automatic control system artificial neural network neural network training |
| url | http://ijournal-as.com/jour/index.php/ijas/article/view/177 |
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