• DocumentCode
    1929694
  • Title

    Missing sensor data restoration for vibration sensors on a jet aircraft engine

  • Author

    Narayanan, Sreeram ; Vian, J.L. ; Choi, J.J. ; Mark, R.J. ; El-Sharkaw, M.A. ; Thompson, Benjamin B.

  • Author_Institution
    Boeing Phantom Works, Boeing Co., Seattle, WA, USA
  • Volume
    4
  • fYear
    2003
  • fDate
    20-24 July 2003
  • Firstpage
    3007
  • Abstract
    Using array historical data, the readings from a sensor array may be shown to contain sufficient redundancy such that the readings from one or more lost sensors may be able to be accurately estimated from those remaining. This interdependency can be established by an neural network encoder. The encoder is also used in the restoration process. In this paper, we give some examples of sensor restoration for vibration sensors on jet engine and computer traffic data.
  • Keywords
    aircraft computers; encoding; jet engines; neural nets; vibration measurement; auto-associative regression machine; computer traffic data; jet aircraft engine; missing sensor data restoration; neural network encoder; vibration sensors; Aircraft propulsion; Computational intelligence; Frequency response; Imaging phantoms; Intelligent sensors; Jet engines; Neural networks; Sensor arrays; Testing; Vibration measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2003. Proceedings of the International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7898-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2003.1224050
  • Filename
    1224050