摘要
针对国内某大型钢铁企业4^#高炉钒钛矿冶炼的实际情况，根据已开发的静态模型分析了4^#高炉冶炼过程的规律和定量关系。并通过分析影响炉缸热制度的主要因素及普通矿冶炼热制度与钒钛矿热制度的差别来研究4^#高炉炉缸热制度特点，提出了以化学热-铁水[Ti]含量代替物理热来判断炉温的变化。在此基础上，通过建立BP神经网络模型和ARIMA模型实现了铁水[Ti]含量的预报。试验结果表明。其预报精度满足实际需要。
According to the actual situation of Vanadium Perovskite smelting of 4# blast furnace of a large domestic iron and steel enterprises,it put forward the chemical heat that the Ti content of hot metal instead of physical heat to judge changes of temperature of the blast furnace.In accordance with the development of static model ,it analyzes the law and the quantitative relationship of smelting process of 4# blast furnace.By analyzing the major factors of the impact of heat system of hearth and the difference between the smelting heat system of general ore and the heat system of vanadium perovskite,it studys the characteristics of the heat system of hearth of 4# blast furnace.Then it puts forward the chemical heat that the Ti content of hot metal instead of physical heat to judge changes of temperature of blast furnace.On this basis,by establishing BP neural network and ARIMA model,iron content of Ti forecasting is achieved.The experimental results show that its forecasting accuracy can meet the actual needs.
出处
《长江大学学报（自科版）（上旬）》
CAS
2008年第3期81-83,97,共4页
JOURNAL OF YANGTZE UNIVERSITY (NATURAL SCIENCE EDITION) SCI ＆ ENG
