A nonlinear prediction model, incorporating mass transfer theory and expert rules, for refining low-carbon ferrochrome

Abstract

SYNOPSIS We present an optimal oxygen-blowing system with expert rules to improve the efficiency of refining low-carbon ferrochrome. A nonlinear model based on mass transfer theory, the principles of heat transfer, and the principles of high-temperature chemical reactions for refining low-carbon ferrochrome are established. The model is mainly used to control the oxygen supply rate during argon-oxygen top-bottom double-blown refining, thereby controlling the refining temperature and reducing the carbon content. Twenty production tests using a 5 t argon-oxygen refining furnace demonstrate the effectiveness of the system and reliability of the nonlinear model. A comparison of the model data with the experimental data shows that although the model fails to predict the silicon content in the final refined product, it can predict the contents of the main components at the refining end-point and the refining temperature accurately. Keywords: prediction model, end-point control, mass transfer theory, expert rules.