The Mars Express (MEX) spacecraft has been orbiting Mars since 2004. The operators need to constantly monitor its behavior and handle sporadic deviations (outliers) from the expected patterns of measurements of quantities that the satellite is sending to Earth. In this paper, we analyze the patterns of the electrical power consumption of MEX’s thermal subsystem, that maintains the spacecraft’s temperature at the desired level. The consumption is not constant, but should be roughly periodic in the short term, with the period that corresponds to one orbit around Mars. By using long short-term memory neural networks, we show that the consumption pattern is more irregular than expected, and successfully detect such irregularities, opening possibility for automatic outlier detection on MEX in the future.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Discovering outliers in the Mars Express thermal power consumption patterns


    Contributors:


    Publication date :

    2021-07-01


    Size :

    4322110 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Machine Learning for Predicting Thermal Power Consumption of the Mars Express Spacecraft

    Petkovic, Matej / Boumghar, Redouane / Breskvar, Martin et al. | IEEE | 2019


    Predicting Thermal Power Consumption of the Mars Express Satellite with Machine Learning

    Breskvar, Martin / Kocev, Dragi / Levatic, Jurica et al. | IEEE | 2017


    Predicting Venus Express Thermal Power Consumption

    Penedones, Hugo / Sousa, Bruno / Donati, Alessandro et al. | AIAA | 2008


    Discovering Mars

    NTRS | 1992


    Mars Express and Venus Express Power Subsystem In-Flight Behaviour

    Loche, D. / European Space Agency | British Library Conference Proceedings | 2008