The Converter Steelmaking End Point Prediction Model Based on RBF Neural Network

被引：7

作者：

Dong, Xianliang ^{[1
]}

Dong, Shi ^{[2
]}

机构：

[1] Liaoning Inst Sci & Technol, Benxi 117000, Peoples R China

[2] Shenyang Jianzhu Univ, Shenyang 110000, Peoples R China

来源：

APPLIED DECISIONS IN AREA OF MECHANICAL ENGINEERING AND INDUSTRIAL MANUFACTURING | 2014年 / 577卷

关键词：

Converter steelmaking; End-point Prediction; RBF Neural Network; Gaussian function;

D O I：

10.4028/www.scientific.net/AMM.577.98

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

The mathematical model of convert steelmaking end point prediction model based on RBF(Radical Basis Function) is presented in this paper. According to the end point prediction problem of the converter steelmaking production prediction problem, we establish the forecast model of converter steelmaking process which describes the relationship between variables such as hot metal quality, oxygen blowing, the quality of the cooling agent and additives etc. and the end point molten steel temperature and carbon content. The prediction system is multidimensional and nonlinear. The model between variables and the target is unknown. For this situation, this paper applies RBF neural network to forecast target, establishing the prediction model based on RBF neural network. So as to obtain the variables and the mathematical model between steel endpoint temperature and carbon content.

引用

页码：98 / +

页数：2