An Intelligent Integrated Predictive Method Based on Gas Temperature Profile for Burn-through Point
基于烟气温度场分布的烧穿点智能集成预测方法

The features of the lead-zinc imperial sintering process include strong nonlinearity,time variance,large time delay,and so on.Based on an analysis of heat state,the gas temperature profile for the sintering apparatus was investigated;a soft-sensor model of the burn-through point(BTP)was developed.Technological-parameter-based and time-sequence-based predictive models that take the dynamic features of the BTP into account were established;they were designed using neural networks and grey theory,respectively.Then,based on the concept of intelligent integration, the synthesis and coordination of these two models was implemented through a fuzzy classifier.The results of actual runs show that intelligent integration provides a practical and effective way of predicting the BTP,which,in turn,serves as a basis for implementing state optimization in the lead-zinc sintering process.