ANOMALY DETECTION METHOD FOR SPACECRAFTS BASED ON ASSOCIATION RULE MINING

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Author(s)

    • YAIRI Takehisa
    • Research Center for Advanced Science and Technology, University of Tokyo
    • KATO Yoshikiyo
    • Research Center for Advanced Science and Technology, University of Tokyo
    • HORI Koichi
    • Research Center for Advanced Science and Technology, University of Tokyo

Abstract

This paper proposes a novel anomaly detection method for spacecraft systems based on data-mining techniques. This method automatically constructs a system behavior model in the form of a set of rules by applying pattern clustering and association rule mining to the time-series data obtained in the learning phase, then detects anomalies by checking the subsequent on-line data with the acquired rules. A major advantage of this approach is that it requires little a priori knowledge on the system.

Journal

  • The Journal of Space Technology and Science

    The Journal of Space Technology and Science 17(1), 1-10, 2001-03-01

    Japanese Rocket Society

References:  5

Codes

  • NII Article ID (NAID)
    10008495118
  • NII NACSIS-CAT ID (NCID)
    AA10925183
  • Text Lang
    ENG
  • Article Type
    ART
  • ISSN
    0911551X
  • Data Source
    CJP  J-STAGE 
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