摘要
分析了原料煤的变质程度、黏结性指标和矿物质含量等性质以及炼焦温度、结焦时间等工艺条件在炼焦过程中对焦炭质量产生的影响,总结了焦炭质量预测模型的研究现状。对基于回归分析法和神经网络等智能算法的预测模型以及改进后预测模型的优缺点进行了评价,最后对焦炭预测模型的发展方向和研究重点进行了展望。
In the coking process, the properties of feed coal （metamorphic grade, caking property index and mineral content）, and coking technological conditions （temperature and coking time） would both influence the coke quality. In this paper, the research status of coke quality prediction model had been summarized. The prediction model based on regression analysis method and neural network intelligent algorithm were predicted, as well as the merits and demerits of improved prediction models. At last, the developing direction and research emphasis of coke quality prediction model were prospected.
出处
《煤质技术》
2014年第1期41-43,共3页
Coal Quality Technology
关键词
焦炭性质
焦炭质量
预测模型
coke properties
coke quality
prediction model
