Title
Just-in-time learning for cement free lime prediction with empirical mode decomposition and database monitoring index
Abstract
Free lime (f-Cao) content is the key quality indicator in the control and optimization of cement calcination process. However, the cement process has many complex characteristics including large noise, time delay, nonlinearity, and time-varying system. To cope with the above characteristics, this study proposes just-in-time (JIT) learning with empirical mode decomposition (EMD) and database monitoring index (DMI) for free lime prediction. At first, EMD and Savitzky-Golay (S-G) filter can effectively deal with process large noise. Meanwhile, weighted time series analysis and mutual information are used to estimate large time delay. Then, least squares support vector machine (LSSVM) based on JIT and DMI is employed to solve the problems of process nonlinearity and time variation. The proposed strategy is validated on practical data from a cement plant.
Year
Venue
Keywords
2019
2019 12th Asian Control Conference (ASCC)
free lime,just-in-time learning,empirical mode decomposition,database monitoring index
Field
DocType
ISSN
Time series,Nonlinear system,Lime,Least squares support vector machine,Computer science,Calcination,Mutual information,Cement,Database,Hilbert–Huang transform
Conference
2072-5639
ISBN
Citations 
PageRank 
978-1-7281-0263-4
0
0.34
References 
Authors
6
4
Name
Order
Citations
PageRank
Jinquan Zheng100.34
Wenli Du217930.50
Weimin Zhong37914.18
Feng Qian4805.46