铜闪速熔炼过程冰铜品位预测模型的研究与应用

A Prediction Model for Matte Grade in Copper Flash Smelting Process

针对铜闪速熔炼过程中的冰铜品位在线检测难题,在组元分析的基础上,研究了独立化学反应以及组分间的摩尔数关系,并建立了数学模型;但由于反应机理的复杂性与建模时的简化,冰铜品位预测精度难以满足实际应用的要求.同时基于工业数据,建立了神经网络冰铜品位预测模型,它能很好地描述训练样本数据之间的关系,但泛化能力不强.为克服单一模型的局限性,引入了包含自适应调整隶属度函数的模糊协调器;将数学模型和神经网络模型有机结合,提出了一种冰铜品位智能集成预测模型.工业数据验证了模型的有效性.

Considering the difficulty of on-line measurement of matte grade in copper flash smelting process and based on analysis of the components, the independent chemical reaction and the molar relationship among components are studied and a mathematical model is presented. Due to the modeling simplifications and complexity of the reaction mechanism, the matte grade prediction precision of the mathematical model can not satisfy the needs of practical applications. Then based on industrial running data, a neural network predictive model for matte grade is established, which can satisfactorily describe the relationship among the training sample data but has low generalization ability. In order to overcome the limitations of single model, a fuzzy coordinator with an adaptively adjustable membership function is introduced, and an intelligent integrated prediction model is proposed, which integrates mathematical model with neural network model. Industrial running results validate the effectiveness of the presented model.