• DocumentCode
    2063681
  • Title

    Distributed prognostic health management with gaussian process regression

  • Author

    Saha, Sankalita ; Saha, Bhaskar ; Saxena, Abhinav ; Goebel, Kai

  • Author_Institution
    MCT/NASA ARC, Moffett Field, CA, USA
  • fYear
    2010
  • fDate
    6-13 March 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. 12A major challenge encountered in such design is formulation of optimal distributed prognostics algorithms. In this paper, we present a distributed GPR based prognostics algorithm whose target platform is a wireless sensor network. In addition to challenges encountered in a distributed implementation, a wireless network poses constraints on communication patterns, thereby making the problem more challenging. The prognostics application that was used to demonstrate our new algorithms is battery prognostics. In order to present trade-offs within different prognostic approaches, we present comparison with the distributed implementation of a particle filter based prognostics for the same battery data.
  • Keywords
    Gaussian processes; aerospace industry; battery management systems; condition monitoring; particle filtering (numerical methods); regression analysis; wireless sensor networks; Gaussian process regression; battery prognostics; communication pattern; distributed GPR based prognostics algorithm; distributed prognostic health management; distributed prognostics architecture design; optimal distributed prognostics algorithm; particle filter; wireless sensor network; Algorithm design and analysis; Batteries; Clustering algorithms; Computer architecture; Gaussian processes; Ground penetrating radar; Intelligent sensors; NASA; Sensor systems; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2010 IEEE
  • Conference_Location
    Big Sky, MT
  • ISSN
    1095-323X
  • Print_ISBN
    978-1-4244-3887-7
  • Electronic_ISBN
    1095-323X
  • Type

    conf

  • DOI
    10.1109/AERO.2010.5446841
  • Filename
    5446841