Bed Permeability State Prediction Model of Sintering Process Based on Data Mining Technology

Abstract

The bed permeability state prediction model of sintering process based on data mining technology was proposed in this study. Firstly, the sintering production data were analyzed by fuzzy clustering algorithm, to make a comprehensive evaluation of the bed permeability state. Then the prediction model of bed permeability state was established via support vector machine, based on the sample data that obtained in the cluster analysis. The bed permeability prediction model has a good learning and generalization ability, its prediction hit rate reached 87.5%. The practical application showed that: the sintering process could be stabilize effectively, since the operation parameters was adjusted according to the prediction results of bed permeability state; the standard deviation of burn through temperature and burn through point was decreased by 47% and 34% respectively.