BOF steelmaking endpoint control based on neural network

Abstract

BOF steelmaking is a kind of paramount steelmaking method. The endpoint control is an important operation in the later period of BOF steelmaking. Because the temperature is very high in the smelting, it is very difficult to take measurement accurately and timely. There is not method to form common feedback control. The BOF endpoint temperature and carbon content were predicted by means of RBF neural network. On the basis of this, the dynamic endpoint control method based on neural network was proposed so as to determine the blown oxygen and the added coolant during the reblowing. The shortcoming that the control model based on the heat balance and the oxygen balance was not accurate in the traditional method was overcome. The endpoint hitting ratio was raised.