Hot metal temperature prediction in blast furnace using advanced model based on fuzzy logic tools

被引：52
|
作者：
Martin, R. D.
Obeso, F.
Mochon, J.
Barea, R.
Jimenez, J.
机构：
[1] Ctr Nacl Invest Met, E-28040 Madrid, Spain
[2] Arcelor, Verina 33208, Gijon, Spain
来源：
IRONMAKING & STEELMAKING | 2007年 / 34卷 / 03期
关键词：
blast furnace; fuzzy logic; hot metal temperature; simulation; prediction;
D O I：
10.1179/174328107X155358
中图分类号：
TF [冶金工业];
学科分类号：
0806 ;
摘要：
The present work presents a model based on fuzzy logic tools to predict and simulate the hot metal temperature in a blast furnace (BF). As input variables this model uses the control variables of a current BF such as moisture, pulverised coal injection, oxygen addition, mineral/coke ratio and blast volume, and it yields as a result of the hot metal temperature. The variables employed to develop the model have been obtained from data supplied by current sensors of a Spanish BF In the model training stage the adaptive neurofuzzy inference system and the subtractive clustering algorithms have been used.
引用
收藏
页码：241 / 247
页数：7
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