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SQualTrack: A Tool for Robust Fault Detection

One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system’s behavior, obtained from the measurements, and the model’s behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper

© IEEE Transactions on Systems, Man, and Cybernetics : Part B: Cybernetics, 2009, vol. 39, p. 475-488

IEEE

Author: Armengol Llobet, Joaquim
Vehí, Josep
Sainz, Miguel Ángel
Herrero i Viñas, Pau
Gelso, Esteban Reinaldo
Date: 2009
Abstract: One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system’s behavior, obtained from the measurements, and the model’s behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper
Format: application/pdf
Citation: Armengol, J., Vehí, J., Sainz, M.A., Herrero, P., i Gelso, E.R. (2009). SQualTrack: A Tool for Robust Fault Detection. IEEE Transactions on Systems, Man, and Cybernetics : Part B: Cybernetics, 39, 2, 475-488. Recuperat 08 juny 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4717262
ISSN: 1083-4419
Document access: http://hdl.handle.net/10256/2562
Language: eng
Publisher: IEEE
Collection: Reproducció digital del document publicat a: http://dx.doi.org/10.1109/TSMCB.2008.2006909
Articles publicats (D-EEEiA)
Is part of: © IEEE Transactions on Systems, Man, and Cybernetics : Part B: Cybernetics, 2009, vol. 39, p. 475-488
Rights: Tots els drets reservats
Subject: Anàlisi d’intervals (Matemàtica)
Control de processos
Errors de sistemes (Enginyeria)
Sistemes d’ajuda a la decisió
Sistemes dinàmics diferenciables
SQualTrack
Interval analysis (Mathematics)
Decision support systems
Differentiable dynamical systems
Process control
System failures (Engineering)
Title: SQualTrack: A Tool for Robust Fault Detection
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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