Sinter ore quality directly affects the stability of blast furnace production. In terms of both physical and chemical properties, the main indicators of sinter quality are the TFe content, alkalinity, and drum index. By analyzing the massive historical data on the sinter production of a steel company, this study proposes a sinter quality prediction system based on Granger causality analysis and a stacking integration algorithm. First, based on real historical data of sintering production in steel enterprises (including coal gas pressure, ignition temperature, combustion air pressure, etc.), data preprocessing of raw data was carried out using a combination of feature engineering and the sintering process. Second, Pearson correlation analysis, Spearman correlation analysis, and Granger causality analysis were used to screen out the characteristic parameters with a strong influence on the target variable of sinter quality (drum Index, TFe, alkalinity). Third, a prediction model for sinter quality parameters was developed using a stacking integration algorithm pair for training. Finally, a program development tool was used to realize the establishment and online operation of a sinter ore quality prediction system. The test results showed that the predicted goodness of fit of the model for the TFe content, alkalinity (R), and drum index were 0.942, 0.958, and 0.987, respectively, and the model calculation time met the actual production requirements. By establishing a suitable model and running the program online, the real-time prediction of the main indicators of sinter quality was realized to guide production promptly.

Low sintering flue gas temperatures and large temperature fluctuations require the development of low-temperature and efficient SCR (selective catalytic reduction) catalysts suitable for the sintering process. It has been shown that modified Mn-Ce/TiO₂ catalysts have good denitration capability and have potential commercial use. In this experiment, TiO₂-loaded Mn and Ce SCR catalysts were prepared using the impregnation method, and a series of characterizations of the samples were carried out to illustrate the effect of the active material on the denitration efficiency. The kinetic analysis provides theoretical as well as data support for the subsequent optimization of the SCR catalysts. The results show that the denitration efficiency of the catalysts can reach 93.86% when the Mn content is 10% and the Ce content is 3%. The doping of active substances can increase the specific surface area, total pore volume and average aperture of the catalysts and improve the adsorption capacity of the catalysts.

In order to obtain the quantitative model of hearth activity, the key control parameters of hearth activity were mined based on big data technology, the distribution characteristics of slag-iron-coke in deadman and the change of voidage in deadman were analyzed, and then the quantitative model of hearth activity was constructed. The results show that a temperature ratio was selected as the characterization parameter of hearth activity combined with some manifestations when the hearth activity became poor, through data sensitivity analysis. Blast speed, average particle size of coke, binary basicity of slag and Ti in iron were preliminarily selected as the key control parameters based on data correlation. The distribution of slag-iron-coke in hearth showed that the average particle size, CSR of coke and the fluidity of slag iron were very important for hearth activity. The coke particle size and the blast momentum should be given priority consideration according to the voidage of deadman in hearth. Finally, the quantitative model of hearth activity was constructed, the accuracy of the model was verified through the data of a commercial BF, so the hearth activity of any BF can be calculated by substituting the known production data of BF.

This study aims to explore the influence mechanism of interfacial reaction in BF. The interfacial reaction behavior was analyzed, the thermodynamic and evolution processes of interfacial reaction were studied, and the influence of interfacial reaction on BF was discussed. The results show that: The desulfurization reaction mechanism can be considered as the electron transfer at slag-iron interface. The viscosity of molten iron shows a decreasing trend with the increase of sulfur content, and the surface tension of molten iron will rapidly decrease with sulfur content, so the interfacial reaction rate will be accelerated. The reduction of FeO occurs at slag-carbon interface, the content of FeO in slag often shows a decreasing trend along the height direction of BF, the erosion rate of carbon brick will increase under the condition of slag with high FeO content. The reduction of SiO₂ is achieved with the help of two gas-phase compounds SiO and SiS. The average Si content in molten iron decreases with the increase of BF volume, which indicates that the large BF is more conducive to achieving low-carbon smelting. The reduction of TiO₂ is carried out at the slag-carbon interface step by step, the valence state of Ti element gradually decreases. The iron-carbon interface in hearth has a significant effect on the erosion of carbon brick and the state of hearth. The wetting and erosion process at iron-carbon interface is clarified based on the cycle model, the carbon brick is eroded in this cycle. The time for the carburization of molten iron is limited, so the carbon content of molten iron cannot reach saturation, although there are a large number of iron-carbon interfaces in hearth. The change trend of maximum temperature on sidewall is opposite to the actual carbon content, the change in carburization behavior at iron-carbon interface is the essential reason for the fluctuation of erosion rate of carbon brick.