Hybrid Modeling for Soft Sensing of Molten Steel Temperature in LF  

作　　者：TIAN Hui-xin MAO Zhi-zhong WANG An-na 

机构地区：[1]School of Electrical and Automation Engineering, Tianjin Polytechnic University, Tianjin 300160, China [2]School of Information Science and Engineering, Northeastern University, Shenyang 110004, Liaoning, China [3]Key Laboratory of Integrated Automation of Process Industry of Ministry of Education, NortheasternUniversity, Shenyang 110004, Liaoning, China

出　　处：《Journal of Iron and Steel Research International》2009年第4期1-6,共6页

基　　金：Item Sponsored by National Natural Science Foundation of China (50474086,60843007)

摘　　要：Aiming at the limitations of traditional thermal model and intelligent model, a new hybrid model is established for soft sensing of the molten steel temperature in LF. Firstly, a thermal model based on energy conservation is described; and then, an improved intelligent model based on process data is presented by ensemble ELM （extreme learning machine） for predicting the molten steel temperature in LF. Secondly, the self-adaptive data fusion is pro- posed as a hybrid modeling method to combine the thermal model with the intelligent model. The new hybrid model could complement mutual advantage of two models by combination. It can overcome the shortcoming of parameters obtained on-line hardly in a thermal model and the disadvantage of lacking the analysis of ladle furnace metallurgical process in an intelligent model. The new hybrid model is applied to a 300 t LF in Baoshan Iron and Steel Co Ltd for predicting the molten steel temperature. The experiments demonstrate that the hybrid model has good generalization performance and high accuracy.Aiming at the limitations of traditional thermal model and intelligent model, a new hybrid model is established for soft sensing of the molten steel temperature in LF. Firstly, a thermal model based on energy conservation is described; and then, an improved intelligent model based on process data is presented by ensemble ELM （extreme learning machine） for predicting the molten steel temperature in LF. Secondly, the self-adaptive data fusion is pro- posed as a hybrid modeling method to combine the thermal model with the intelligent model. The new hybrid model could complement mutual advantage of two models by combination. It can overcome the shortcoming of parameters obtained on-line hardly in a thermal model and the disadvantage of lacking the analysis of ladle furnace metallurgical process in an intelligent model. The new hybrid model is applied to a 300 t LF in Baoshan Iron and Steel Co Ltd for predicting the molten steel temperature. The experiments demonstrate that the hybrid model has good generalization performance and high accuracy.

关 键 词：ladle furnace hybrid modeling soft sensing thermal model data fusion 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TF777[自动化与计算机技术—计算机科学与技术]