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Aggregating Models for Anomaly Detection in Space Systems: Results from the FCTMAS Study

  • Francesco Amigoni
  • Maurizio Ferrari Dacrema
  • Alessandro Donati
  • Christian Laroque
  • Michèle Lavagna
  • Alessandro Riva
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 867)

Abstract

The Flight Control Team Multi-Agent System (FCTMAS) study, funded by the European Space Agency (ESA), has investigated the use of multiagent systems in supporting flight control teams in routine operations. One of the scientific challenges of the FCTMAS study has been the detection of anomalies relative to a space system only on the basis of identified deviations from the nominal trends of single measurable variables. In this paper, we discuss how we addressed this challenge by looking for the best structure that aggregates a given set of models, each one returning the anomaly probability of a single measurable variable, under the assumption that there is no a priori knowledge about the structure of the space system nor about the relationships between the variables. Experiments are conducted on data of the Cryosat-2 satellite and their results are eventually summarized as a set of guidelines.

Notes

Acknowledgment

The authors kindly acknowledge the contributions of Matteo Gallo and Matteo Garza to the development of the MCS Subsystem described in this paper.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Francesco Amigoni
    • 1
  • Maurizio Ferrari Dacrema
    • 1
  • Alessandro Donati
    • 2
  • Christian Laroque
    • 3
  • Michèle Lavagna
    • 1
  • Alessandro Riva
    • 1
  1. 1.Politecnico di MilanoMilanItaly
  2. 2.European Space Agency (ESA), Advanced Mission Concepts and Technologies OfficeDarmstadtGermany
  3. 3.Telespazio Vega Deutschland GmbHDarmstadtGermany

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