基于小波分析理论的指数平滑模型预测自然陈化中钢渣f-CaO含量  

Forecast on f-CaO Content in Steel Slag with Natural Aging by Exponential Smoothing Model Based on Wavelet Analysis

作　　者：张浩[1] 杨刚[2] 刘秀玉[1] 刘影[1] 朱庆明[1] 

机构地区：[1]安徽工业大学建筑工程学院,安徽马鞍山243032 [2]中冶宝钢技术服务有限公司,上海200941

出　　处：《过程工程学报》2015年第4期555-558,共4页The Chinese Journal of Process Engineering

基　　金：国家自然科学基金资助项目(编号:41301644);高等学校优秀青年人才基金项目(编号:2010SQRL034)

摘　　要：采用自然陈化方法处理滚筒钢渣,跟踪检测渣中游离氧化钙（f-CaO）含量,分析f-CaO含量变化机理;运用小波分析理论和指数平滑模型建立了指数平滑模型,预测滚筒钢渣自然陈化过程中f-CaO含量.结果表明,自然陈化方法可有效降低滚筒钢渣中f-CaO含量,A类滚筒钢渣自然陈化180 d后f-CaO含量约为1.2%,B类滚筒钢渣自然陈化60 d后f-CaO含量为5.0%-6.0%,满足安全利用要求;基于小波分析理论的指数平滑模型的预测值与实验值吻合较好,相对误差为-3.442%-4.651%,有效提高了滚筒钢渣自然陈化中f-CaO含量预测精度.Natural aging method was used to deal with Baosteel short-flow （BSSF） steel slag, content of free CaO （f-CaO） in BSSF steel slag monitored, and the change mechanism analyzed. Exponential smoothing model based on wavelet analysis was established by wavelet analysis theory and exponential smoothing method to forecast the f-CaO content of steel slag in natural aging. The results showed that f-CaO content of BSSF steel slag was effectively reduced by natural aging method to meet the requirements of safe use, namely f-CaO content in type A steel slag was about 1.2% after 180 d and in type B steel slag about 5.0%-6.0 % after 60 d. Exponential smoothing model based on wavelet analysis predicted data agreed well with the experimental data, the relative error was -3.442%-4.651%, it could increase the prediction accuracy efficiently of the f-CaO content of steel slag in natural aging.

关 键 词：自然陈化 滚筒钢渣 预测 小波分析理论 指数平滑模型 游离氧化钙 

分 类 号：TQ172.622[化学工程—水泥工业]