电弧炉炼钢炉渣成分实时预报模型

Real-time prediction model of slag composition in electric arc furnace steelmaking

为了实现冶炼过程中对炉渣成分的实时预测,给电弧炉炼钢过程中加料等工艺操作提供帮助,对影响炉内炉渣成分的因素(炉内反应、加料与流渣)进行了研究,构建了电弧炉炼钢炉渣成分实时预报模型.结果显示,该模型能够实时预测炉内炉渣质量和成分变化,预报炉内铁元素氧化状况,可为冶炼过程中添加辅料与流渣等工艺操作提供指导作用.通过与现场炉渣取样检测结果进行对比,得到炉渣中CaO、SiO2和FeO实测成分与模型预测成分的平均相对误差分别为12.66%、11.17%和19.16%.

To realize the real-time prediction of slag composition in the smelting process and provide the assistance to the operations in electric arc furnace(EAF)steelmaking process such as charging,the influence factors on the slag composition in the furnace(furnace reaction,charging,and slag overflowing)were studied,and the real-time prediction model of slag composition in EAF steelmaking process was established.In the results,the model could predict the slag quality,the slag composition,and the oxidation status of Fe element in the furnace in real time,providing the guidance for the auxiliary material charging and the slag flowing in the smelting process.Compared with the slag sampling results,the average relative errors of CaO,SiO2,and FeO content in the slag between the actual measurement and the model predicted values were 12.66%,11.17%,and 19.16%,respectively.