Keywords
roasting process
control system
automation
temperature control
energy efficiency
digital monitoring
intelligent technologies
How to Cite
Abstract
This study focuses on the analysis of the control system for the roasting process of sulfide-containing products. The physico-chemical characteristics of the process are examined, including temperature regulation, oxygen concentration, and gas flow stability. The main chemical reactions, heat transfer mechanisms, and factors contributing to improved energy efficiency are identified. Mathematical modeling and parameter optimization methods aimed at minimizing exhaust gas emissions are also presented.
In the study, a comprehensive analysis of the control system for the roasting process of sulfide-containing products was carried out based on scientific data and the practices of modern metallurgical production. Sulfide ores of copper, zinc, and iron were examined, and their physico-chemical and thermophysical properties during roasting were studied. Theoretical analysis, technological modeling, and investigation of the principles of automated control were applied. The obtained results made it possible to identify the main factors influencing the stability, energy efficiency, and environmental safety of the process.
As a result of the conducted research, the possibility of optimizing the roasting process of sulfide ores through an automatic control system has been proven. The physicochemical analysis revealed the influence of temperature and oxygen concentration on the reaction rate. Heat exchange analysis showed that heat losses in the furnace account for 12–15%. After the implementation of the PID controller, temperature fluctuations decreased by 81%, and SO₂ concentration variations by 80%. Energy consumption was reduced by 15%, while raw material consumption decreased by up to 8%. The process stability, energy efficiency, and environmental safety improved significantly.
The analyses carried out have shown that in existing roasting systems, heat losses, insufficient temperature stability, and uncertainties in controlling the composition of exhaust gases reduce process efficiency. To eliminate these shortcomings, it is recommended to improve thermal insulation, optimize the energy balance, and apply adaptive or fuzzy logic algorithms in the control system. The implementation of predictive analysis functions in the SCADA system will enable proactive process control and help reduce energy consumption. Based on the proposed approaches, the roasting process can become more stable, energy-efficient, and environmentally safe.
References
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