A Soft Sensing Method for Operation Optimization of Coke Dry Quenching Process
作者单位：School of Mechatronical Engineering and AutomationShanghai UniversityShanghai Key Lab of Power Station Automation Technology Department of Chemical Engineering“Tsing-Hua University” Shanghai Baosight Software Co Ltd
会议名称：《第36届中国控制会议》
会议届次：36
主办单位：Dalian University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
会议日期：2017年
学科分类：081702[工学-化学工艺] 08[工学] 0817[工学-化学工程与技术]
关 键 词：Soft sensor Coke dry quenching Data-driven Variable selection Autoregressive integrated moving average
摘 要：Based on the actual data analysis, it is found in this paper that the supplementary air flow rate in the CDQ operation didn’t follow the variation of the discharge rate of incandescent coke well, which results in the concentration increase of combustible gas in the exhaust gas and the decrease of economic efficiency. The correlation analysis results show that the introduced derived variables are more useful than some plain variables for the purpose of prediction. Next, to handle the contradiction between the steam productivity and the coke burning loss, a new economic efficiency index is introduced by synthesizing the two competing aspects. A kind of soft sensor of economic efficiency is put forward by combining nonnegative garrote（NNG） variable selection algorithm with the autoregressive integrated moving average（ARIMA） model, which gives a good solution to the economic efficiency real-time prediction problem of CDQ system. Then, the implementation of model-based optimization is studied based on the actual operation data. The results show that there exists large room for economic efficiency promotion.