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A Multiple Sensor Fault Detection Method based on Fuzzy Parametric Approach

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 24))

Abstract

This paper presents a new approach for the model-based diagnosis. The model is based on an adaptation with a variable forgetting factor. The variation of this factor is managed thanks to fuzzy logic. Thus, we propose a design method of a diagnosis system for the sensor defaults. In this study, the adaptive model is developed theoretically for the Multiple-Input Multiple-Output (MIMO) systems. We present the design stages of the fuzzy adaptive model and we give details of the Fault Detection and Isolation (FDI) principle. This approach is validated with a benchmark: a hydraulic process with three tanks. Different defaults (sensors) are simulated with the fuzzy adaptive model and the fuzzy approach for the diagnosis is compared with the residues method. The method is efficient to detect and isolate one or more defaults. The results obtained are promising and seem applicable to a set of MIMO systems.

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Lafont, F., Pessel, N., Balmat, JF. (2009). A Multiple Sensor Fault Detection Method based on Fuzzy Parametric Approach. In: Filipe, J., Cetto, J.A., Ferrier, JL. (eds) Informatics in Control, Automation and Robotics. Lecture Notes in Electrical Engineering, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85640-5_3

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  • DOI: https://doi.org/10.1007/978-3-540-85640-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85639-9

  • Online ISBN: 978-3-540-85640-5

  • eBook Packages: EngineeringEngineering (R0)

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