摘要
钢坯加热过程是钢铁企业热轧生产中非常重要的工艺环节。钢坯温度预报模型是实现加热炉优化控制的重要基础,用常规仪器很难直接测量出钢坯温度。给出了基于RBF神经网络的软测量模型结构,对钢坯温度进行预报的仿真结果。
Heating process is part of iron and steel enterprise's hot-rolled which is very important.The model to predict the temperature of steel slab is an important part for realizing optimize control.It is difficult to measure slab's temperature directly by general instrument.This paper offers the model structure of soft-sensing based on RBF neural network.
出处
《工业控制计算机》
2010年第5期73-75,共3页
Industrial Control Computer
关键词
加热炉
RBF神经网络
软测量
钢坯温度
reheating furnace
RBF neural network
soft-sensing
temperature of steel slab