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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。
The ferric ion concentration at reactor exit during the goethite precipitation process can not be detected on-line, affecting the real-time optimal control of the production process. Therefore, it is necessary to establish a bivalent iron ion concentration prediction model, based on the input conditions such as system inlet parameters and control parameters, to predict the ferric ion concentration at the outlet of the reactor. Based on chemical reaction kinetics theory and experimental research, the structure of predictive model is established. For the parameters which are difficult to be determined in the model, the actual production data with a large number of working conditions are used to identify. The sensitivity of parametric model is analyzed by parameter output sensitivity matrix, and the sensitivity information is introduced into the objective function of model parameter identification to improve the identification accuracy of model parameters. The simulation results show that the prediction model has a clear physical meaning, the prediction results can well track the fluctuation of production data in the field, and the accuracy of the model can meet the production needs.