Soft sensing of the burning through point in iron-making process

Abstract

In the iron-making process, the state of burning through point (BTP) is the closure of sintering which is one of the most important parameters in judging the state of sintering. Based on the PSO (Particle Swarm Optimization)-inversion soft-sensing method, the BTP which can not be directly measured in the iron-making process is soft-sensed in this paper. Firstly, the principle of sintering is studied. Four parameters are employed to forecast the BTP, including the suction pressure of main chimney flue, air input, velocity of sintering machine and ignition temperature. And then, a prediction model using PSO is established. At last, the model is applied to production process. It is proved to be effective.