电弧炉炼钢厂钢水成分与温度预报模型的研究  

Research on the Molten Steel Components and Temperature Forecast Model for EAF Steelmaking Plant

作　　者：杨凌志[1] 朱荣[1] 宁建成[1,2] 宋景凌[2] 韦波[2] 

机构地区：[1]北京科技大学冶金与生态工程学院,北京100083 [2]衡阳华菱钢管有限公司,湖南衡阳421000

出　　处：《工业加热》2013年第1期15-17,20,共4页Industrial Heating

摘　　要：基于实际生产数据分析研究影响钢水成分与温度的因素,通过利用BP神经网络的理论,建立了钢水成分与温度预报模型,实现了提前对钢水成分与温度的预报。钢水成分预报值与实测值基本吻合,钢水温度预报的命中率在84.0%以上,模型具有较高的预报精度。On the basis of the practical production data,the factors affecting the components and temperature of molten steel were analyzed,and by using BP neural network theory,the molten steel components and temperature forecast model was established,which realized the composition and temperature of molten steel forecast.The difference between forecast value and actual value for the molten steel components is small,and the shooting of the molten steel temperature forecast is 84.0% above,so the model has high precision of forecast.

关 键 词：电弧炉 成分 温度 预报 模型 

分 类 号：TF741.5[冶金工程—钢铁冶金]