| Iron and steel, the most important structural material and functional material in 20th century, will continue its output increasing in China in 21st century. As the upper procedure of iron and steel industry, Blast Furnace (BF) ironmaking is an important integral part of this pillar industry in national economy. Technical development in ironmaking is critical to the development of iron and steel industry and energy saving. Due to its high complexity, the automation of ironmaking is a difficult technical problem in the field of metallurgy automation. The most difficult part is to predict and exercise control beforehand under instable BF status. Only when exact forecast is fulfilled can the automation of intelligent control be realized.The simulation in this paper is based on previous research of fuzzy Bayes network. After detailed computation and analysis, a combined predictive model for silicon content in hot metal is proposed and attains good result. It is a solid requirement to keep both current and future iron making status smooth. Considering the timeliness and time delay of control operations to the silicon content in hot metal, the model of curves by cross thermometer is also discussed and taken into consideration to guide the BF foreman. All data is collected from Handan Steel No.7 B.F of 2000m~3.It is a hybrid research of mathematical theory, reaction dynamics, hydrodynamics and operation mechanism of BF ironmaking process. The two models constructed have been put into application and proved to be successful.
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