Model of Hot Metal Silicon Content in Blast Furnace Based on Principal Component Analysis Application and Partial Least Square  

作　　者：SHI Lin LI Zhi-ling YU Tao LI Jiang-peng 

机构地区：[1]School of Mathematics, Physics and Biological Engineering, University of Science and Technology Inner Mongolia, Baotou 014010, Inner Mongolia, China [2]School of Information Engineering, University of Science and Technology Inner Mongolia, Baotou 014010, Inner Mongolia, China

出　　处：《Journal of Iron and Steel Research International》2011年第10期13-16,共4页

基　　金：Item Sponsored by National Natural Science Foundation of China(51064019);Natural Science Foundation of Inner Mongolia of China(20010MS0911,NJzy08075)

摘　　要：In blast furnace （BF） iron-making process, the hot metal silicon content was usually used to measure the quality of hot metal and to reflect the thermal state of BF. Principal component analysis （PCA） and partial least- square （PLS） regression methods were used to predict the hot metal silicon content. Under the conditions of BF rela- tively stable situation, PCA and PLS regression models of hot metal silicon content utilizing data from Baotou Steel No. 6 BF were established, which provided the accuracy of 88.4% and 89.2%. PLS model used less variables and time than principal component analysis model, and it was simple to calculate. It is shown that the model gives good results and is helpful for practical production.In blast furnace （BF） iron-making process, the hot metal silicon content was usually used to measure the quality of hot metal and to reflect the thermal state of BF. Principal component analysis （PCA） and partial least- square （PLS） regression methods were used to predict the hot metal silicon content. Under the conditions of BF rela- tively stable situation, PCA and PLS regression models of hot metal silicon content utilizing data from Baotou Steel No. 6 BF were established, which provided the accuracy of 88.4% and 89.2%. PLS model used less variables and time than principal component analysis model, and it was simple to calculate. It is shown that the model gives good results and is helpful for practical production.

关 键 词：hot metal silicon content partial least square principal component analysis temperature prediction 

分 类 号：TF748[冶金工程—钢铁冶金] TP311.52[自动化与计算机技术—计算机软件与理论]