Hybrid Modeling of Molten Steel Temperature Prediction in LF

Abstract

Combining the conventional mechanism method with the newly developed intelligent algorithm, a hybrid model was developed for predicting the molten steel temperature in LF. The mechanism method is used to build the thermal model by analyzing the energy going into and out of the molten steel during the LF refining production process. It is hard to calculate the coefficients in the thermal model by mechanism method, so they are estimated by experience traditionally. In this paper, a new ensemble ELM algorithm using the modified AdaBoost.RT is proposed to calculate these coefficients. The new hybrid model overcomes the difficulty of obtaining the coefficients in thermal model, and solves the problem of limited prediction precision using “black box” model. The experiment demonstrates that the new hybrid model can improve generalization performance and the prediction accuracy.