Predictive control of Si content in blast furnace smelting based on improved SA-BP

Blast furnace smelting process is a highly complex nonlinear dynamic process, its purpose is to refining the quality of liquid iron. From the point of view of chemical reaction kinetics, the main chemical reactions in the blast furnace are as many as 108 kinds, and the high complexity is obvious. From the point of view of hydrodynamics, there are three-phase mixed compressible viscous fluids in the blast furnace smelting process. The hydrodynamic equation is nonlinear, high-dimensional and high-coupling. In addition, the blast furnace smelting process has the characteristics of time-varying, high-dimensional, distributed parameters and other characteristics of the complex conditions and the failure of the operation under the conditions of the test, making the blast furnace smelting process automation and furnace temperature precision control to become metallurgical workers face the problem. In this study, from the data point of view, to explore the furnace temperature can be characterized by [Si] content prediction. Based on the data of 1000 furnace blast furnace, an accurate and reasonable prediction model of Si content in blast furnace is established. First of all, through the calculation of correlation coefficients of various factors and the time trend diagram, the general lag time between each parameter and Si content in the process of blast furnace production is obtained. Through correlation and analysis of the correlation between lag time, before and after the two largest furnace, with improved simulated annealing algorithm to determine the optimal initial weights, the content of Si, the N furnace of S content, the quantity of coal and air PML FL as input, the contents of Si in n+1 furnace as output to establish dynamic prediction model of improved SA-BP neural network based. Finally, the data used to detect the model is brought into the model to be tested, the error is analyzed, and the error local map is used to express the error visually. The model is tested.

MODELING OF DISTRIBUTION COEFFICIENTS OF CHARGE ELEMENTS BETWEEN FINISHED PRODUCTS OF BLAST FURNACE SMELTING IN MODERN CONDITIONS

The results of using the developed methodology for predicting the distribution coefficients of the charge elements between the products of blast-furnace smelting based on the calculation of the integral parameters of the charge and the temperature-blowing regime for modern operating conditions of one of the blast furnaces in Ukraine are presented. The proposed approach differs from traditional methods of considering the distribution coefficients of charge elements as constant values and provides a predictive calculation of the chemical composition of cast iron and slag depending on specific charge and technological conditions when solving the problem of a reasonable choice of the composition of the blast furnace charge.

Influence of Type and Consumption of Pellets on Indicators of Blast-Furnace Smelting in the JSC Ural Steel

The article presents the results of the analysis of production data on the operation of the blast furnace No. 1 of Ural Steel JSC for the period from 2013 to 2018. During this period, the Mikhailovsky GOK pellets with different basicities were used. It has been established, that the effectiveness of the use of pellets of different basicities is determined by their behavior in a blast furnace and depends on the proportion of pellets in the iron ore part of the charge. The gas-dynamic conditions of melting deteriorate with an increase in the proportion of pellets in the charge, which is accompanied by an increase in the specific pressure drop and forces the blast rate, to be adjusted. It is necessary to work on 40-45% of fluxed pellets and 20-25% acid pellets in a charge at a blast rate of 2000-2100 m3/min, to minimize coke rate and increase rate of work of blast furnace No. 1 of Ural Steel JSC. An increase in pellet consumption is possible while maintaining the efficiency of blast-furnace smelting only if their high-temperature properties are improved, as a result of optimization of basicity and increase in MgO content, which affects the structure and properties of the silicate binder.

Processing of Agglomerates and Pellets Containing Various Amounts of Titanium Dioxide

Questions about the oxidative roasting of iron ore raw materials (agglomerates and pellets) are studied. Features of the phase structure of the iron ore raw materials containing titan and vanadium are discussed. Reducibility, durability, and the softening and melting temperatures of metallurgical iron ore raw materials are studied in vitro. The objects of the research are titaniferous ores containing different amounts of titan dioxide. The behaviors of agglomerates and pellets in a blast furnace are studied, and the influence of their physical and chemical properties on heat and mass transfer processes are researched by means of a mathematical model. The main indices of blast furnace smelting—productivity, coke consumption, composition of top gas, cast iron, and slag—are shown. It is established that the increase in titanium dioxide content in pellets, as the amount of concentrate with increased TiO2 content increases, does not cause deterioration in the quality of iron ore raw materials being prepared for blast furnace smelting. At the same time, as the hot strength of raw materials increases, the temperature at which softening begins increases and the temperature interval of softening of materials decreases.

Physical-Chemical and Pyrometallurgical Estimation of Processing of Complex Ores with Extraction of Iron, Vanadium, Titanium

The metallurgical characteristics of pellets (reducibility, strength after reaction, softening start and end temperatures), phase composition (X-ray phase analysis), and porosity were studied. Blast furnace smelting parameters were calculated using laboratory pellets with different basicities and degrees of metallization. Pellets were obtained from complex titanium-magnetite ores. The vanadium extraction of this ore into metal did not exceed 10 % during smelting of metallized pellets in an arc steelmaking furnace, but special techniques could raise this to 85 %. According to calculations from the Institute of Metallurgy of the Ural Branch of the Russian Academy of Sciences (IMET UB RAS), vanadium extraction up to 80–90 % can be achieved by using high-base and partially metallized pellets. The influence of changes in the composition and metallurgical characteristics of titanomagnetite pellets with increasing basicity (especially relative to strength after reduction) should be taken into account.