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Detection and Diagnosis of Plant-Wide Oscillations

Authors

  • M. A. A. Shoukat Choudhury,

    1. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada T6G 2G6
    Current affiliation:
    1. Department of Chemical Engineering, Bangladesh University of Engineering & Technology, BUET, Dhaka-1000, Bangladesh
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  • Vinay Kariwala,

    1. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada T6G 2G6
    Current affiliation:
    1. Division of Chemical and Biomolecular Engineering, Nanyang Technological University, Singapore 637722
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  • Nina F. Thornhill,

    1. Centre for Process Systems Engineering, Department of Electronic and Electrical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
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  • Hisato Douke,

    1. Mitsubishi Chemical Corporation, 3–10 Ushiodori, Kurashiki, Okayama 712-8054, Japan
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  • Sirish L. Shah,

    Corresponding author
    1. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada T6G 2G6
    • Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada T6G 2G6
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  • Haruo Takada,

    1. Mitsubishi Chemical Corporation, 3–10 Ushiodori, Kurashiki, Okayama 712-8054, Japan
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  • J. Fraser Forbes

    1. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada T6G 2G6
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  • A preliminary version of this work was presented at the Advanced Process Control Applications for Industry Workshop held in Vancouver, BC, Canada in 2004. An expanded version of the contents of “Confi rming Stiction” in the “Oscillation Diagnosis” section was presented at the 16th IFAC World Congress in Prague, Czech Republic, in 2005.

Abstract

This paper presents some emerging techniques for detection and root-cause diagnosis of plant-wide oscillations, and demonstrates their efficacy through a successful industrial case study. The recently proposed autocorrelation function based method (Thornhill et al., J. Proc. Control 13, 91–100, 2003a) is used for detection of oscillations in the process measurements. Signals having common oscillations are analyzed for the presence of valve stiction using higher order statistical methods (Choudhury et al., Automatica 40, 1719–1728, 2004b). A method employing changes in controller gain is proposed for distinguishing an internally generated oscillation from an external oscillatory disturbance. This method of changing controller gain is used to confirm the presence of control valve stiction. The proposed techniques have been used successfully to identify the root cause of plant-wide oscillations in an industrial case study using routine operating data.

Abstract

On présente dans cet article des techniques émergentes pour la détection et le diagnostic intrinsèques des oscillations à l'échelle de l'usine et on démontre leur efficacité à travers une étude de cas industrielle réussie. On a recours à une méthode proposée récemment qui repose sur la fonction d'autocorrélation (Thornill et al., J. Proc. Control 13, 91-100, 2003a) pour la détection des oscillations dans les mesures de procédés. Les signaux ayant des oscillations communes sont analysés pour déterminer la présence de friction statique des vannes par des méthodes statistiques d'ordres supérieurs (Choudhury et al., Automatica 40, 1719-1728, 2004b). On propose une méthode employant des changements dans le gain du contrôleur pour distinguer une oscillation générée à l'intérieur du système à partir d'une perturbation oscillatoire externe. Cette méthode de changement du gain du contrôleur est utilisée pour confirmer la présence de friction statique dans les vannes de régulation. Les techniques proposées sont utilisées avec succès pour déterminer les raisons intrinsèques des oscillations à l'échelle de l'usine dans une étude de cas industrielle utilisant des données opératoires de routine.

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