Fault detection in processes represented by PLS models using an EWMA control scheme

Handle URI:
http://hdl.handle.net/10754/622404
Title:
Fault detection in processes represented by PLS models using an EWMA control scheme
Authors:
Harrou, Fouzi; Nounou, Mohamed N.; Nounou, Hazem N.
Abstract:
Fault detection is important for effective and safe process operation. Partial least squares (PLS) has been used successfully in fault detection for multivariate processes with highly correlated variables. However, the conventional PLS-based detection metrics, such as the Hotelling's T and the Q statistics are not well suited to detect small faults because they only use information about the process in the most recent observation. Exponentially weighed moving average (EWMA), however, has been shown to be more sensitive to small shifts in the mean of process variables. In this paper, a PLS-based EWMA fault detection method is proposed for monitoring processes represented by PLS models. The performance of the proposed method is compared with that of the traditional PLS-based fault detection method through a simulated example involving various fault scenarios that could be encountered in real processes. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS method.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Harrou F, Nounou MN, Nounou HN (2016) Fault detection in processes represented by PLS models using an EWMA control scheme. 2016 International Conference on Control, Decision and Information Technologies (CoDIT). Available: http://dx.doi.org/10.1109/CoDIT.2016.7593552.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2016 International Conference on Control, Decision and Information Technologies (CoDIT)
Conference/Event name:
3rd International Conference on Control, Decision and Information Technologies, CoDIT 2016
Issue Date:
20-Oct-2016
DOI:
10.1109/CoDIT.2016.7593552
Type:
Conference Paper
Sponsors:
The authors gratefully acknowledge financial support from Qatar National Research Fund, National Priorities Research Fund grant number NPRP-7-1172-2-439.
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorHarrou, Fouzien
dc.contributor.authorNounou, Mohamed N.en
dc.contributor.authorNounou, Hazem N.en
dc.date.accessioned2017-01-02T09:28:29Z-
dc.date.available2017-01-02T09:28:29Z-
dc.date.issued2016-10-20en
dc.identifier.citationHarrou F, Nounou MN, Nounou HN (2016) Fault detection in processes represented by PLS models using an EWMA control scheme. 2016 International Conference on Control, Decision and Information Technologies (CoDIT). Available: http://dx.doi.org/10.1109/CoDIT.2016.7593552.en
dc.identifier.doi10.1109/CoDIT.2016.7593552en
dc.identifier.urihttp://hdl.handle.net/10754/622404-
dc.description.abstractFault detection is important for effective and safe process operation. Partial least squares (PLS) has been used successfully in fault detection for multivariate processes with highly correlated variables. However, the conventional PLS-based detection metrics, such as the Hotelling's T and the Q statistics are not well suited to detect small faults because they only use information about the process in the most recent observation. Exponentially weighed moving average (EWMA), however, has been shown to be more sensitive to small shifts in the mean of process variables. In this paper, a PLS-based EWMA fault detection method is proposed for monitoring processes represented by PLS models. The performance of the proposed method is compared with that of the traditional PLS-based fault detection method through a simulated example involving various fault scenarios that could be encountered in real processes. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS method.en
dc.description.sponsorshipThe authors gratefully acknowledge financial support from Qatar National Research Fund, National Priorities Research Fund grant number NPRP-7-1172-2-439.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectDatabased fault detectionen
dc.subjectEWMAen
dc.subjectMean shiften
dc.subjectPartial least squaresen
dc.subjectProcess monitoringen
dc.titleFault detection in processes represented by PLS models using an EWMA control schemeen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2016 International Conference on Control, Decision and Information Technologies (CoDIT)en
dc.conference.date2016-04-06 to 2016-04-08en
dc.conference.name3rd International Conference on Control, Decision and Information Technologies, CoDIT 2016en
dc.conference.locationSaint Julian's, MLTen
dc.contributor.institutionTexas AandM University at Qatar, Chemical Engineering Program, United Statesen
dc.contributor.institutionElectrical and Computer Engineering Program, Texas AandM University at Qatar, United Statesen
kaust.authorHarrou, Fouzien
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