Billet temperature intelligent prediction and furnace temperature optimal setting of regenerative reheating furnace

被引：0

作者：

Liu Xiao-zhi ^{[1
]}

Zhao Zhong-lei ^{[1
]}

Qin Shu-kai ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Peoples R China

来源：

Proceedings of the 2007 Chinese Control and Decision Conference | 2007年

关键词：

regenerative reheating furnace; mathematic model; genetic algorithm; furnace temperature optimal setting;

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：

Based on the heat radiation and mathematics method of finite difference method of unsteady heat conduction, a billet temperature prediction model is designed by using one-dimension unsteady heat conduction method. The strategy of furnace temperature optimal setting based on this model is also presented. Global optimization with genetic algorithms is used to determine the unknown parameters and thus a bad prediction is avoided. The model can give a grid of billet temperature prediction, the online forecasting for the distribution of billet temperature in furnace can be achieved. Moreover, simulations results show that the model has high precision and the optimal setting of furnace temperature can greatly improve the billets heat quality.

引用

页码：147 / 150

页数：4