• DocumentCode
    2273660
  • Title

    Discovering Atypical Flights in Sequences of Discrete Flight Parameters

  • Author

    Budalakoti, Suratna ; Srivastava, Ashok N. ; Akella, Ram

  • Author_Institution
    University of California, Santa Cruz, suratna@soe.ucsc.edu
  • fYear
    2006
  • fDate
    4-11 March 2006
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper describes the results of a novel research and development effort conducted at the NASA Ames Research Center for discovering anomalies in discrete parameter sequences recorded from flight data. Many of the discrete parameters that are recorded during the flight of a commercial airliner correspond to binary switches inside the cockpit. The inputs to our system are records from thousands offlights for a given class of aircraft and destination. The system delivers a list of potentially anomalous flights as well as reasons why the flight was tagged as anomalous. This output can be analyzed by safety experts to determine whether or not the anomalies are indicative of a problem that could be addressed with a human factors intervention. The final goal ofthe system is to help safety experts discover significant human factors issues such as pilot mode confusion, i. e., a flight in which a pilot has lost situational awareness as reflected in atypicality of the sequence of switches that he or she throws during descent compared to a population of similar flights. We view this work as an extension of Integrated System Health Management (ISHM) where the goal is to understand and evaluate the combined health of a class of aircraft at a given destination.
  • Keywords
    Aerospace safety; Aircraft; Bioinformatics; Event detection; Human factors; Intrusion detection; NASA; Sensor systems; Supervised learning; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2006 IEEE
  • Print_ISBN
    0-7803-9545-X
  • Type

    conf

  • DOI
    10.1109/AERO.2006.1656109
  • Filename
    1656109