Data-driven design of monitoring and diagnosis systems for dynamic processes: A review of subspace technique based schemes and some recent results

•The development of data-driven design of process monitoring and fault diagnosis (PM-FD) systems is reviewed.•A data-driven design framework for observer-based PM-FD systems is sketched and finally.•Some recent results are presented. In this paper, the development of data-driven design of process mo...

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Bibliographic Details
Published in:Journal of process control 2014-02, Vol.24 (2), p.431-449
Main Author: Ding, S.X.
Format: Article
Language:English
Subjects:
Data-driven methods
Observer-based methods
Parity space
Process monitoring and fault diagnosis
Subspace identification methods
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Summary:•The development of data-driven design of process monitoring and fault diagnosis (PM-FD) systems is reviewed.•A data-driven design framework for observer-based PM-FD systems is sketched and finally.•Some recent results are presented. In this paper, the development of data-driven design of process monitoring and fault diagnosis (PM-FD) systems is reviewed and some recent results are presented. A major objective of this work is to sketch a process input–output data based framework of designing PM-FD systems for dynamic processes. The main focus of our study is on the data-driven design of observer-based PM-FD systems, which are, thanks to their high robustness and real-time ability, suitable for industrial applications.
ISSN:0959-1524
1873-2771
DOI:10.1016/j.jprocont.2013.08.011