A Model for Steel Billet Temperature of Prediction of Heating Furnace

被引：0
|
作者：
Chen Youwen [1 ,2 ]
Chai Tianyou [1 ]
机构：
[1] Northeastern Univ, Key Lab Proc Ind Automat, Minist Educ & Liaoning Prov, Shenyang 110819, Peoples R China
[2] Jiuquan Iron & Steel Corp, Jiuquan 735100, Peoples R China
来源：
PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE | 2010年
关键词：
Heating Furnace; Extreme Learning Machine (ELM); Forecast of Billet Temperature; Particle Swarm Optimize (PSO); EXTREME LEARNING-MACHINE; FEEDFORWARD NETWORKS; CONSUMPTION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The estimate of main guide line of steel billet temperature is all along a puzzle in the industry due to the fact that heating furnace is a multivariable nonlinear system with large inertia, net lag and crossed coupling. This thesis proposes billet predictive model between billet temperature variable and heating process variable with improved ELM method. At last, based on actual data from steel industry, reckon model parameter. Analyzing check and error indicate that this model can forecast the temperature of entrance for billet steel before 10 similar to 25 minutes, and the error of prediction can satisfy the demand for industrial application.
引用
收藏
页码：1299 / 1302
页数：4
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