Reconstruction-based contribution for process monitoring

Authors:
Carlos F. Alcala;S. Joe Qin
Affiliations:
Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA;Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA and Ming Hsieh Department of Electrical Engineering, University ...
Venue:
Automatica (Journal of IFAC)
Year:
2009

Citing 1
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Automatica (Journal of IFAC)

Brief paper: Geometric properties of partial least squares for process monitoring

Automatica (Journal of IFAC)
Chemical process fault diagnosis based on sensor validation approach

ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I

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Abstract

This paper presents a new method to perform fault diagnosis for data-correlation based process monitoring. As an alternative to the traditional contribution plot method, a reconstruction-based contribution for fault diagnosis is proposed based on monitored indices, SPE, T^2 and a combined index @f. Analysis of the diagnosability of the traditional contributions and the reconstruction-based contributions is performed. The lack of diagnosability of traditional contributions is analyzed for the case of single sensor faults with large fault magnitudes, whereas for the same case the proposed reconstruction-based contributions guarantee correct diagnosis. Monte Carlo simulation results are provided for the case of modest fault magnitudes by randomly assigning fault sensors and fault magnitudes.