Thermal Characterization and Simulation of the Iron Ore Sintering Process

Abstract

Accurately identifying the state of the sintering process and stably controlling the sintering endpoint are fundamental challenges that cannot be bypassed in the iron ore sintering process .In this study, by analyzing the temperature and concentration of flue gas emitted during the four stages of preheating, combustion, sintering, and cooling in the sintering process, optimizing the parameters of the Gaussian emission distribution using forward-backward and Baum-Welch algorithms, and dynamically tracking the transition path of the sintering thermal state using a Viterbi decoding strategy, a numerical characterization method for sintering states based on a Gaussian HMM model is proposed. The computational results indicate that the model demonstrates high discrimination capability across the preheating, sintering, and cooling stages, with F1 scores all exceeding 0.98. The model achieves a calculation accuracy of up to 96.63% for sintering thermal states, providing reliable support for the accurate identification of thermal states during the sintering process.