无钟高炉螺旋布料料面预测与优化控制研究  

Research on burden surface prediction and optimal control of spiral charging at bell-less top blast furnace

作　　者：马财生 韩骏[2] 杨二旭 张志达 任廷志 

机构地区：[1]燕山大学国家冷轧板带装备及工艺工程技术研究中心,河北秦皇岛066004 [2]秦皇岛首秦金属材料有限公司,河北秦皇岛066326

出　　处：《燕山大学学报》2017年第6期503-509,共7页Journal of Yanshan University

基　　金：国家科技支撑计划资助项目(2011BAF15B01);秦皇岛市科技支撑计划项目(201703A021)

摘　　要：为实现无钟高炉布料精准化,提出了一种螺旋布料料面预测与优化控制算法。根据炉料在高炉炉喉内的堆积规律,建立了适用于非接触式料面测量技术的炉喉料面预测模型。在螺旋布料工艺特点研究的基础上,建立了螺旋布料操作优化控制数学模型,并设计了粒子群算法进行模型求解。最后,该模型采用有效容积为2 580 m^3的无钟高炉进行了试验验证,结果表明,采用基于粒子群算法的螺旋布料优化控制模型能够准确地获得期望的炉料分布,充分发挥无钟高炉布料灵活的优势。An optimal control method is developed to achieve accurate spiral charging based on particle swarm optimization. Based on the law of heap formation in the furnace throat,a model for burden surface prediction is established,which adapts to the improvement of the non-contact burden surface measurement technology. Based on the spiral charging characteristics,a mathematical model for spiral charging optimal control is established,and the particle swarm optimization is designed for model solving. Finally,the model is verified in an actual blast furnace whose effective volume is around 2 580 m^3. The results show that the optimal control model based on particle swarm optimization is able to obtain expected burden distribution accurately and give full play to the advantages of device flexibility.

关 键 词：无钟高炉 螺旋布料 料面预测 优化控制 粒子群算法 

分 类 号：TF543.3[冶金工程—钢铁冶金]