• DocumentCode
    571672
  • Title

    The Application of Wavelet Transform to Fault Detection of Aircraft Control Surface

  • Author

    Chen, Xiao ; Wang, Xinmin ; Peng, Cheng

  • Author_Institution
    Coll. of Autom., Northwestern Poly-Tech. Univ., Xi´´an, China
  • Volume
    2
  • fYear
    2012
  • fDate
    26-27 Aug. 2012
  • Firstpage
    324
  • Lastpage
    327
  • Abstract
    Control surface failure which can change the structure of the motion equations is a difficult problem in fault detection. To this failure, the wavelet analysis method is presented to detect fault signal in accordance with wavelet local refinement properties. Wavelet basis selection is one of the key issues in the wavelet analysis method. According to the rules of the wavelet basis, a proper selection is given. Subsequently, fault detection algorithm based on wavelet transform is proposed. Finally, simulation is carried out based on the stuck of elevator of F16 fighter. In the process of simulation, wavelet basis db4 is selected and Mallat algorithm, 3-layer decomposition is adopted. The results show that wavelet analysis method can effectively detect the fault occurrence time.
  • Keywords
    aircraft control; fault diagnosis; wavelet transforms; 3-layer decomposition; F16 fighter; Mallat algorithm; aircraft control surface; control surface failure; elevator; fault detection; fault occurrence time; fault signal; wavelet analysis method; wavelet basis db4; wavelet basis selection; wavelet local refinement properties; wavelet transform; Fault detection; Signal processing algorithms; Surface waves; Vectors; Wavelet analysis; Wavelet transforms; Control Surface; Fault Detection; Multi-scale Analysis; Wavelet Transform; Wavelet basis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
  • Conference_Location
    Nanchang, Jiangxi
  • Print_ISBN
    978-1-4673-1902-7
  • Type

    conf

  • DOI
    10.1109/IHMSC.2012.173
  • Filename
    6305787