INTELLIGENT SYSTEM FOR CONTROLLING THE ELECTRONIC POWER OF ORE-THERMAL FURNACES BASED ON PROGRAMMABLE CONTROLLERS

The article discusses the development of an intelligent control system for the electric power of oresmelting furnaces based on programmable logic controllers (PLC). Control of electric power in ore-smelting furnaces is a complex task associated with the need to optimize energy consumption and increase productivity while minimizing equipment wear. The proposed control system is based on the use of PLCs in combination with artificial intelligence algorithms, which allows for monitoring and automatic regulation of furnace operating parameters in real time.The purpose of this work is to create a control system that can adapt to changing furnace operating conditions, optimizing the energy consumption process and improving the stability of the system. The article also presents methods for integrating PLCs with sensors that provide data collection, as well as analysis and forecasting algorithms based on neural network technologies. The study shows that the implementation of such a control system can significantly reduce energy consumption, reduce the load on electrical equipment and improve the overall efficiency of the ore-smelting furnace.Experimental data and a comparative analysis of the furnace operation before and after the implementation of the intelligent control system are presented. The results show that the intelligent control system using PLC can improve process stability, reduce operating costs and extend the service life of equipment.

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Publication Details

Journal
Bulletin of Shakarim University Technical Sciences
Published
2024-12-27
DOI
https://doi.org/10.53360/2788-7995-2024-4(16)-4
Primary Topic
Industrial Engineering and Technologies
Type
article
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article

INTELLIGENT SYSTEM FOR CONTROLLING THE ELECTRONIC POWER OF ORE-THERMAL FURNACES BASED ON PROGRAMMABLE CONTROLLERS

Bulgyn Mailykhanova, Sh. K. Koshimbayev
Bulletin of Shakarim University Technical Sciences
Industrial Engineering and Technologies
article

INTELLIGENT SYSTEM FOR CONTROLLING THE ELECTRONIC POWER OF ORE-THERMAL FURNACES BASED ON PROGRAMMABLE CONTROLLERS

Bulgyn Mailykhanova, Sh. K. Koshimbayev
article en

Abstract

The article discusses the development of an intelligent control system for the electric power of oresmelting furnaces based on programmable logic controllers (PLC). Control of electric power in ore-smelting furnaces is a complex task associated with the need to optimize energy consumption and increase productivity while minimizing equipment wear. The proposed control system is based on the use of PLCs in combination with artificial intelligence algorithms, which allows for monitoring and automatic regulation of furnace operating parameters in real time.The purpose of this work is to create a control system that can adapt to changing furnace operating conditions, optimizing the energy consumption process and improving the stability of the system. The article also presents methods for integrating PLCs with sensors that provide data collection, as well as analysis and forecasting algorithms based on neural network technologies. The study shows that the implementation of such a control system can significantly reduce energy consumption, reduce the load on electrical equipment and improve the overall efficiency of the ore-smelting furnace.Experimental data and a comparative analysis of the furnace operation before and after the implementation of the intelligent control system are presented. The results show that the intelligent control system using PLC can improve process stability, reduce operating costs and extend the service life of equipment.

Bulletin of Shakarim University Technical SciencesVol. 1(4(16))
Satbayev University (KZ), Almaty Technological University (KZ)
Openalex Percentile: Top 73%
Industrial Engineering and Technologies
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INTELLIGENT SYSTEM FOR CONTROLLING THE ELECTRONIC POWER OF ORE-THERMAL FURNACES BASED ON PROGRAMMABLE CONTROLLERS — Bulgyn Mailykhanova, Sh. K. Koshimbayev · Bulletin of Shakarim University Technical Sciences (2024) | TGRS Research Map | TGRS