Abstract

The aim of the work is to increase the level of automation of blast furnace production through the development and implementation of new systems to support decision-making on the management of blast furnace smelting in changing technological and fuel conditions. The article presents a description of three decision support systems (DSS) in the mode of an adviser to the technological personnel of blast furnaces, which were implemented by the Iron and Steel Institute or underwent pilot testing as part of the automated control system of the blast furnace shop of the metallurgical production of PrJSC "Dniprovskyi Coke Plant" (Kamianske). The first DSS for managing the thermal state was implemented in 2021, it includes the entire list of information necessary for personnel in a convenient and compact form, generates recommendations in case of technology deviations and, in case of incorrect actions of the personnel, signals the need for correct actions. The main recommendations of the system are to correct the raceway adiabatic flame temperature, coke consumption when its characteristics and ore load change. Using the system allows both reducing the specific coke consumption and preventing unplanned downtime. The second DSS for controlling the distribution of fuel additives over air tuyeres is based on information on thermal loads determined on water-cooled elements of tuyere tools. The main recommendations of the system are to adjust the amount of injected pulverized coal fuel on individual tuyeres in order to ensure a uniform distribution of the raceway adiabatic flame temperature around the circumference of the blast furnace and, as a result, the energy efficiency of blast furnace smelting. The third DSS for adjusting the parameters of the charging mode is based on information from the means of controlling the temperatures of the gas flow above the surface of the charge in the blast furnace. The functioning of this system is based on determining the reference curves for the distribution of the gas flow along the furnace radii, corresponding to the minimum consumption of coke and maximum productivity, and on the search for solutions by direct and iterative optimization methods, which allow, by adjusting the loading parameters, to ensure a rational distribution of charge materials and gas flow in the furnace.

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