高炉硅含量预测控制的时间序列混合建模

根据时间序列原理，对铁水硅质量分数w(Si)序列的动态特性进行了分析，找出了其主体成分.综合炼铁工艺理论和6号高炉炼铁现场的实际情况，对影响铁水硅质量分数w(Si)的各个因素进行了典型相关分析，确定了w(Si)的主要影响因素为：料速、风量、喷煤、透气性、富氧率、铁水物理温度和渣碱度.建立了由AR(2)、状态变量和控制变量混合构成的w(Si)预测控制的传递函数模型.使用包钢6号高炉生产数据验证表明，此模型克服了以往炉温控制模型把炼铁理论和统计知识分离的缺点，炉温预报的命中率高达84%，预测控制取得了较好的效果.

Hybrid time series predictive control model for silicon content in blast furnace hot metal

Based on principle of time series analysis,the dynamic characteristic of silicon content series in molten iron was discussed and the main components were discovered.Integrated the theories of iron-making technique and the situation of Blast Furnace No.6 on-the-spot,canonical correlation analysis(CCA) was used to decide the main influencing parameters of silicon content,eg.lowering speed,blast volume,pulverized coal,permeability,oxygen-enriched,physical temperature of molten iron and basicity.Then a hybrid transfer function model composed of AR(2),state variables and control variables was proposed for predictive control of silicon content.The model was tested using datasets from Blast Furnace No.6 of Baotou Steel Corporation.Simulation showed that the hit rate was over 84%.Thus the predictive control model is effective and economic,and avoids the traditional model's shortcoming of separating the theories of iron-making and statistics.