• DocumentCode
    300613
  • Title

    Fault detection schemes for a diesel engine turbocharger

  • Author

    Ludwig, C. ; Ayoubi, M.

  • Author_Institution
    Inst. of Control Eng., Tech. Univ. Darmstadt, Germany
  • Volume
    3
  • fYear
    1995
  • fDate
    21-23 Jun 1995
  • Firstpage
    2118
  • Abstract
    In this paper two model based methods for real time fault detection of Diesel engine turbochargers are presented and compared. Fault detection schemes which are based on residual generation between the measured and some estimated process states require precise mathematical models of the process. One approach is utilizing parametric nonlinear dynamic models, whereas the other method uses artificial neural networks with distributed dynamics for modeling
  • Keywords
    failure analysis; internal combustion engines; modelling; neural nets; nonlinear dynamical systems; artificial neural networks; diesel engine turbocharger; distributed dynamics; parametric nonlinear dynamic models; real-time fault detection; residual generation; Artificial neural networks; Control engineering; Diesel engines; Electronic mail; Fault detection; Mathematical model; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, Proceedings of the 1995
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-2445-5
  • Type

    conf

  • DOI
    10.1109/ACC.1995.531272
  • Filename
    531272