• DocumentCode
    1769147
  • Title

    Data-driven fault detection design for satellite´s attitude control system

  • Author

    Lijun Song ; Jiongqi Wang ; Zheng Hu ; Haiyin Zhou

  • Author_Institution
    Coll. of Basic Educ., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2014
  • fDate
    24-27 Aug. 2014
  • Firstpage
    237
  • Lastpage
    244
  • Abstract
    The object of this paper is to address data-driven fault detection design for satellite´s attitude control system with different data characteristics, which includes the establishment and the evaluation of the detection statistics. Firstly, a simple T2 detection statistic is constructed for stale data. Then, a mid-value smoothing method based on data-driven is proposed to cope with the unstable data. For the system without baseline data, a predicting and modeling method is applied to generate the residual statistic. Finally, an input-output system identification method is studied to search a model structure for the control system including both tahe control input and the measured output. The proposed approaches are driven by pure data and are evaluated by using an example of a satellite´s attitude control system, and excellent results are obtained.
  • Keywords
    artificial satellites; attitude control; fault diagnosis; identification; smoothing methods; T2 detection statistic; baseline data; data characteristics; data-driven fault detection design; detection statistics; input-output system identification method; mid-value smoothing method; model structure; modeling method; predicting method; residual statistic; satellite attitude control system; stale data; tahe control input; Autoregressive processes; Monitoring; Predictive models; Sensor phenomena and characterization; Sensor systems; Smoothing methods; data smoothing; fault detection; satellite control; system identification; time-series modeling prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Prognostics and System Health Management Conference (PHM-2014 Hunan), 2014
  • Conference_Location
    Zhangiiaijie
  • Print_ISBN
    978-1-4799-7957-8
  • Type

    conf

  • DOI
    10.1109/PHM.2014.6988171
  • Filename
    6988171