Abstract
In blast furnace(BF) iron-making process, it usually used the hot metal silicon content to measure the quality of hot metal and to reflect the thermal state of BF (BF temperature). For better prediction and control of total variance contribution with 87.72% were extracted according to Principal Component Analysis (PCA). A regression model for predictive control of silicon content was established. The model was tested on datasets from BF No.6 in Baotou Steel Corporation and good accuracy was received with 88.4%. According to the model, air volume and air temperature control range could be improved with the influence of molten iron blast furnace silicon content.
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