Forecast on f-CaO Content in Steel Slag with Natural Aging by Exponential Smoothing Model Based on Wavelet Analysis
ZHANG Hao YANG Gang LIU Xiu-yu LIU Ying ZHU Qing-ming
School of Civil Engineering and Architecture, Anhui University of Technology MCC Baosteel Technical Service Center Co. Ltd School of Civil Engineering and Architecture, Anhui University of Technology School of Civil Engineering and Architecture, Anhui University of Technology School of Civil Engineering and Architecture, Anhui University of Technology
Abstract：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.
张浩 杨刚 刘秀玉 刘影 朱庆明. 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[J]. 过程工程学报, 2015, 15(4): 555-558.
ZHANG Hao YANG Gang LIU Xiu-yu LIU Ying ZHU Qing-ming. Forecast on f-CaO Content in Steel Slag with Natural Aging by Exponential Smoothing Model Based on Wavelet Analysis. Chin. J. Process Eng., 2015, 15(4): 555-558.
2015, Vol. 15 
