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.