针铁矿法沉铁过程Fe^(2+)浓度预测建模  

Research on Fe2+ Concentration Prediction Model of Iron Removal Process by Goethite

作　　者：李勇刚[1] 王莎[1] 桂卫华[1] 阳春华[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083

出　　处：《控制工程》2013年第1期38-41,共4页Control Engineering of China

基　　金：国家自然科学基金(60874069);教育部高校博士点专项科研基金(200805331104);中南大学创新学位论文项目基金(2010ssxt199)

摘　　要：针铁矿法沉铁过程中反应器出口的二价铁离子浓度无法在线检测,影响到生产过程的实时优化控制。为此需要建立二价铁离子浓度预测模型,以系统入口参数和控制参数等输入条件为依据,实现预测反应器出口二价铁离子的浓度值。基于化学反应动力学理论与实验研究确立预测模型的结构;对于模型中难以确定的参数,采用蕴含大量工况信息的实际生产数据辨识得到。通过参数输出灵敏度矩阵分析参数模型的敏感度,并将灵敏度信息引入模型参数辨识的目标函数,以提高模型参数的辨识精度。仿真结果表明:预测模型具有较为明确的物理意义,预测结果能很好地跟踪现场生产数据的波动,模型的精度可以满足生产需要。For the ferrous-ion concentration of iron removal process by goethite is impossible to detect on line, affecting the real-time control of the production process, a ferrous-ion concentration prediction model is composed. This model can predict the ferrous-ion con- centration by input parameters and control parameters of system. Based on chemical reaction kinetics and experimental research results the model structure is proposed. The unknown parameters of prediction model can be obtained by parameters identification using actual production data stored much condition information. The sensitivity of the model parameters is analyzed by parameter-output sensitivity matrix, then, sensitivity information is added to parameter optimization objective function. Simulation results show that the output of fer- rous-ion concentration prediction model can track the process data well, and it has satisfactory prediction precision and can be used as strong guidance for optimal control of the goethite process.

关 键 词：针铁矿法沉铁 二价铁离子浓度 预测模型 敏感度分析 参数辨识 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]