%0 Journal Article
%T An Intelligent Integrated Predictive Method Based on Gas Temperature Profile for Burn-through Point<br>基于烟气温度场分布的烧穿点智能集成预测方法
%A WU Min
%A XU Chen-Hua
%A <br>吴敏
%A 徐辰华
%J 自动化学报
%D 2007
%I 
%X 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.
%K Lead-zinc sintering process
%K burn-through point(BTP)
%K gas temperature profile
%K technological-parameter-based predictive model
%K time-sequence-based predictive model
%K integrated predictive model<br>铅锌烧结过程
%K 烧穿点
%K 烟气温度场分布
%K 工艺参数预测模型
%K 时间序列预测模型
%K 集成预测模型
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=AB6D2DBC66BEE95AC8803ACCAABA9C01&yid=A732AF04DDA03BB3&vid=27746BCEEE58E9DC&iid=59906B3B2830C2C5&sid=AF8A4A632EC02431&eid=7E01AF4ED17ED9B3&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=21