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Model-based fault detection in Diesel engines air-path ; Diagnostic à base de modèle de la boucle d'air des moteurs Diesel

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  • معلومة اضافية
    • Contributors:
      IFP Energies nouvelles (IFPEN); GIPSA-Services (GIPSA-Services); Grenoble Images Parole Signal Automatique (GIPSA-lab); Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS); Inria Grenoble - Rhône-Alpes; Institut National de Recherche en Informatique et en Automatique (Inria); Networked Controlled Systems (NECS); Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Département Automatique (GIPSA-DA); Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab); Institut National Polytechnique de Grenoble - INPG; Carlos Canudas de Wit(carlos.canudas-de-wit@gipsa-lab.inpg.fr)
    • بيانات النشر:
      HAL CCSD
    • الموضوع:
      2012
    • Collection:
      Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
    • نبذة مختصرة :
      The study of model-based fault detection for mass production Diesel engines is the aim of this thesis. The necessity of continuous vehicles health monitoring is now enforced by the Euro VI pollutant legislation, which will probably be tightened in its future revisions. In this context developing a robust strategy that could be easily calibrated and work with different systems (due to production variability) would be a tremendous advantage for car manufacturers. The study developed here tries to answer to those necessities by proposing a generic methodology based on local adaptive observers for scalar nonlinear state-affine systems. The fault detection, isolation and estimation problems are thus solved in a compact way. Moreover, the uncertainties due to measurement or model biases and time drifts lead to the necessity of improving the detection methodology by the use of robust thresholds that could avoid undesired false alarms. In this thesis a variable threshold is proposed based on the observability condition and the sensitivity analysis of the parameter impacted by the fault with respect to input or model uncertainties. This approach allows, among other things, to be used as an analysis tool for the individuation of the system operating points for which the diagnosis is more reliable and more robust to inputs uncertainties. The discussed approach has been successfully implemented and experimentally tested on a real Diesel engine for the intake leak detection and for the turbine efficiency loss drift detection in a co-simulation environment showing its advantages in term of detection reliability, calibration effort and engines diagnosis operating condition analysis. ; Cette thèse a pour but l'étude de la détection basée sur modèle de défauts pour les moteurs Diesel produits en grande série. La nécessité d'une surveillance continue de l'état de santé des véhicules est maintenant renforcée par la législation Euro VI sur les émissions polluantes, qui sera probablement rendue encore plus contraignante dans ses ...
    • Relation:
      tel-00757525; https://tel.archives-ouvertes.fr/tel-00757525; https://tel.archives-ouvertes.fr/tel-00757525/document; https://tel.archives-ouvertes.fr/tel-00757525/file/Phd_report_Riccardo_Ceccarelli_2012.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.80085710