• DocumentCode
    2060870
  • Title

    UIO based robust fault diagnosis approach for aero-engine fiber-optic sensor

  • Author

    Chen He ; Xiaodong Zhang ; Binghui Jia

  • Author_Institution
    Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2013
  • fDate
    17-20 Aug. 2013
  • Firstpage
    550
  • Lastpage
    553
  • Abstract
    The purpose of this study is to develop a model-based method for detecting optical fiber sensor fault in aero-engine linear discrete time invariant (LDTI) system considering both disturbances and uncertainties. Firstly, the fiber-optic sensors are analyzed and utilized to measure the aero-engine compressor output and aero-engine compressor is reduced to a 4-input 3-output single-spool state space linear model. Secondly, the discrete robust unknown input observer (DRUIO) is designed for the fault detection based on a linear matrix inequality (LMI) approach. The performance of the observer is demonstrated by applying the design procedure to a nonlinear gas turbine model. And the result shows that less than 2% sensor fault can be detected with disturbance.
  • Keywords
    aerospace engines; compressors; fault diagnosis; fibre optic sensors; gas turbines; linear matrix inequalities; observers; 4-input 3-output single-spool state space linear model; DRUIO design; LDTI system; LMI approach; aeroengine compressor output measurement; aeroengine fiber-optic sensor; aeroengine linear discrete time invariant system; discrete robust unknown input observer design; linear matrix inequality approach; nonlinear gas turbine model; optical fiber sensor fault detection; robust fault diagnosis approach; Fault diagnosis; Mathematical model; Observers; Optical fiber sensors; Optical fibers; Robustness; Temperature measurement; aero-engine compressor model; aero-engine fiber-optic sensor; fault detection; linear matrix inequality (LMI); unknown input observer (UIO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering (CASE), 2013 IEEE International Conference on
  • Conference_Location
    Madison, WI
  • ISSN
    2161-8070
  • Type

    conf

  • DOI
    10.1109/CoASE.2013.6653947
  • Filename
    6653947