Fault detection in an overheads condenser using multivariate SPC

D. J.H. Wilson; G. W. Irwin; G. Lightbody

doi:10.1049/cp:19960568

Fault detection in an overheads condenser using multivariate SPC

D. J.H. Wilson
, G. W. Irwin
, G. Lightbody

Queen's University Belfast

Research output: Contribution to journal › Article › peer-review

Abstract

A statistical model is generated via Partial Least squares, a multivariate statistical modeling technique. Results from simulation studies on an EPSRC-funded benchmark plant, consisting of an overheads condenser and a reflux drum illustrate the success of the approach. Standard statistical process control (SPC) techniques are then used to detect simulated faults by analysis of the mismatch between the PLS model prediction and the original plant.

Original language	English
Pages (from-to)	293-298
Number of pages	6
Journal	IEE Conference Publication
Issue number	427 /1
DOIs	https://doi.org/10.1049/cp:19960568
Publication status	Published - 1996
Externally published	Yes
Event	Proceedings of the 1996 UKACC International Conference on Control. Part 1 (of 2) - Exeter, UK Duration: 2 Sep 1996 → 5 Sep 1996

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10.1049/cp:19960568

Cite this

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title = "Fault detection in an overheads condenser using multivariate SPC",

abstract = "A statistical model is generated via Partial Least squares, a multivariate statistical modeling technique. Results from simulation studies on an EPSRC-funded benchmark plant, consisting of an overheads condenser and a reflux drum illustrate the success of the approach. Standard statistical process control (SPC) techniques are then used to detect simulated faults by analysis of the mismatch between the PLS model prediction and the original plant.",

author = "Wilson, \{D. J.H.\} and Irwin, \{G. W.\} and G. Lightbody",

year = "1996",

doi = "10.1049/cp:19960568",

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AB - A statistical model is generated via Partial Least squares, a multivariate statistical modeling technique. Results from simulation studies on an EPSRC-funded benchmark plant, consisting of an overheads condenser and a reflux drum illustrate the success of the approach. Standard statistical process control (SPC) techniques are then used to detect simulated faults by analysis of the mismatch between the PLS model prediction and the original plant.

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U2 - 10.1049/cp:19960568

DO - 10.1049/cp:19960568

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AN - SCOPUS:0030420987

SN - 0537-9989

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JO - IEE Conference Publication

JF - IEE Conference Publication

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T2 - Proceedings of the 1996 UKACC International Conference on Control. Part 1 (of 2)

Y2 - 2 September 1996 through 5 September 1996

ER -

Fault detection in an overheads condenser using multivariate SPC

Abstract

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