Unevenly Sampled Dynamic Data Modeling and Monitoring With an Industrial Application
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 2203-2213 |
Number of pages | 11 |
Journal / Publication | IEEE Transactions on Industrial Informatics |
Volume | 13 |
Issue number | 5 |
Online published | 2 May 2017 |
Publication status | Published - Oct 2017 |
Externally published | Yes |
Link(s)
Abstract
In this paper, a dynamic modeling method for unevenly sampled data is proposed for the monitoring of bi-layer (i.e., a process layer and a quality layer) dynamic processes. First, a novel uneven data dynamic canonical correlation analysis method with an integrated dynamic time window is proposed for interlayer latent structure modeling, which captures the dynamic relations between regularly sampled process data and quality data with slow and irregular sampling. The new model is a step toward big data modeling to deal with data irregularity and diversity. Second, after extracting covariations using an interlayer model, intralayer variations are extracted using subsequent principal component analysis on the residual subspaces of the original process data and quality data, respectively. Third, a concurrent monitoring method for unevenly sampled bi-layer data is proposed. Finally, the proposed method is demonstrated using an illustrative simulation example and applied successfully to a real blast furnace iron-making process.
Research Area(s)
- Dynamic processes, dynamic canonical correlation analysis (CCA), interlayer and intralayer concurrent monitoring, unevenly sampled data modeling
Citation Format(s)
Unevenly Sampled Dynamic Data Modeling and Monitoring With an Industrial Application. / Liu, Qiang; Qin, S. Joe; Chai, Tianyou.
In: IEEE Transactions on Industrial Informatics, Vol. 13, No. 5, 10.2017, p. 2203-2213.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review