Neural Network Model for Control of Operating Modes of Crushing and Grinding Complex

• Autorzy: Kalinchyk Vasyl , Meita Olexandr , Pobigaylo Vitalii , Borychenko Olena , Kalinchyk Vitalii

Identyfikatory

DOI

10.54740/ros.2022.003

• Języki publikacji: EN

Abstrakty

EN

This article investigates the application of neural network models to create automated control systems for industrial processes. We reviewed and analysed works on dispatch control and evaluation of equipment operating modes and the use of artificial neural networks to solve problems of this type. It is shown that the main requirements for identification models are the accuracy of estimation and ease of algorithm implementation. It is shown that artificial neural networks meet the requirements for accuracy of classification problems, ease of execution and speed. We considered the structures of neural networks that can be used to recognise the modes of operation of technological equipment. Application of the model and structure of networks with radial basis functions and multilayer perceptrons for identifying the mode of operation of equipment under given conditions is substantiated. The input conditions for constructing neural network models of two types with a given three-layer structure are offered. The results of training neural models on the model of a multilayer perceptron and a network with radial basis functions are presented. The estimation and comparative analysis of models depending on model parameters are made. It is shown that networks with radial basis functions offer greater accuracy in solving identification problems. The structural scheme of the automated process control system with mode identification based on artificial neural networks is offered.

Słowa kluczowe

EN

classification; modelling; neural network; radial basis function network; RBF; multilayer perceptron; MLP

• Wydawca: Politechnika Koszalińska
• Czasopismo: Rocznik Ochrona Środowiska
• Rocznik: 2022
• Tom: Tom 24
• Strony: 26--40
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Kalinchyk Vasyl

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

• https://orcid.org/0000-0003-4028-0185

autor

Meita Olexandr

• Department of Electromechanical Equipment of Energy Production, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"

• https://orcid.org/0000-0002-4132-5202

autor

Pobigaylo Vitalii

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

• https://orcid.org/0000-0003-2673-7329

autor

Borychenko Olena

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

autor

Kalinchyk Vitalii

• Department of Labor, Industrial and Civil Safety, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"

• https://orcid.org/0000-0003-3931-646X

Bibliografia

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• Kalinchyk, V., Meita, O., Pobigaylo, V., Kalinchyk, V., Filyanin, D. (2021). Neuromodel of the “Crusher mill” Mechatronic Complex. Rocznik Ochrona Środowiska, 23. 470-483.
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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).