磁选管回收率智能混合预报方法

针对衡量竖炉焙烧过程焙烧矿质量好坏的关键工艺指标磁选管回收率难以在线测量、化验结果滞后的难题，采用神经网络、案例推理和专家系统技术，提出了由神经网络预报模型、案例推理预报模型、自校正模型组成的磁选管回收率智能混合预报模型，讨论了模型的结构、主要功能和实现算法，并成功应用于赤铁矿选矿厂竖炉焙烧过程．应用效果表明，在工况正常与异常两种情况下，所提出的方法均能准确预报磁选管回收率．将磁选管回收率预报模型应用于竖炉焙烧过程的优化控制，使磁选管回收率保持在最优工艺指标范围之内，取得了明显的成效．

Intelligent Hybrid Prediction Method of Magnetic Tube Recovery Rate

Magnetic Tube Recovery Rate(MTRR) is a key technical index used to evaluate roasted iron mine's quality.The value of MTRR is acquired by chemical test,a process that has a big delay and is hard to measure online after shaft furnace roasting process.To deal with this problem,an intelligent hybrid prediction model is developed to predict the MTRR punctually based on the neural networks,case-based reasoning and expert systems.This model consists of a neural network prediction model,a case-based reasoning prediction model,and a self-tuning model.The whole model's framework,the main function and the algorithm implementation are discussed.Application to shaft furnace roasting process of a Minerals Processing Factory show that the model is effective in both normal and abnormal operating conditions.This prediction model has been applied to the optimal control of the roasting process,so that the MTRR can be kept within the optimal ranges,and obvious benefit is achieved.