• DocumentCode
    3442924
  • Title

    Regression based complex equipment Prognostic and Health Management

  • Author

    Guoshun Chen ; Gefang Wang ; Wenbin Cao

  • Author_Institution
    Inst. of Ordnance Technol., Shijiazhuang, China
  • fYear
    2013
  • fDate
    15-18 July 2013
  • Firstpage
    1893
  • Lastpage
    1896
  • Abstract
    A novel Prognostic and Health Management (PHM) method for an Unmanned Air Vehicle (UAV) is proposed. The method uses trend analysis with regression to build the reference indicator, through probability-based techniques, and produce a degradation model to health monitoring UAV system. This method is concerned with trend analysis and regression techniques for estimation of the future condition of the system and prediction of the time-to-failure. The simulation results show that the proposed method can give the health index of UAV visually and is proved to be practical and easy to implement in engineering.
  • Keywords
    autonomous aerial vehicles; condition monitoring; failure analysis; regression analysis; PHM; health index; health monitoring UAV system; probability-based techniques; regression based complex equipment prognostic and health management; time-to-failure prediction; unmanned air vehicle; Analytical models; Degradation; Fuels; Maintenance engineering; Market research; Prognostics and health management; Reliability; Prognostic and Health Management(PHM); Unmanned Aerial Vehicle(UAV); equipment health management; regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-1014-4
  • Type

    conf

  • DOI
    10.1109/QR2MSE.2013.6625949
  • Filename
    6625949