摘要
烧结矿质量指标包括FeO含量、转鼓强度、还原性、低温还原粉化以及软化和熔滴性能等多方面 ,寻求烧结矿质量指标分析的新方法和有效途径是极为必要的。本文通过建立烧结矿质量指标预测的神经网络模型 ,利用实际烧结生产数据对模型进行训练 ,对烧结矿低温还原粉化性能 (RDI)和转鼓强度(TI)
The sinter quality include the content of FeO, drum strength index, reduction index, lower temperature reduction degradation index and meltdown property and etc Therefore, it is necessary to search the analytic and new method and valid path in sinter quality The data from sintering plant are trained through the networks in the prediction of sinter quality Because the space are limited, it only predict drum strength index (TI) and lower temperature reduction degradation index (RDI) of sinter in this paper
出处
《烧结球团》
北大核心
2005年第1期20-22,共3页
Sintering and Pelletizing
