• DocumentCode
    1989667
  • Title

    Aero-generator trend analysis based on optimized grey prediction model

  • Author

    Cui, Jianguo ; Zhao, Pengyuan ; Dong, Shiliang ; Liu, Liqiu ; Lv, Rui ; Li, Zhonghai

  • Author_Institution
    Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China
  • fYear
    2011
  • fDate
    16-18 Sept. 2011
  • Firstpage
    3339
  • Lastpage
    3342
  • Abstract
    In order to accurately analyze the trend of health state variation of aero-generator, a grey prediction model based on genetic algorithm is presented in this paper. Then use the original grey model and the optimized grey model respectively to carry out health state trend analysis of the aero-generator. On this basis, the two models were used to study aero-generator health trends, and compared with the prediction result of the BP neural network, and find suitable algorithms for aero-generator health trend analysis and prediction.
  • Keywords
    avionics; backpropagation; genetic algorithms; grey systems; BP neural network; aero-generator health trend analysis; aero-generator health trends; aero-generator trend analysis; genetic algorithm; health state trend analysis; health state variation; optimized grey model; optimized grey prediction model; Analytical models; Atmospheric modeling; Data models; Genetic algorithms; Mathematical model; Optimization; Predictive models; Aero-generator; Genetic algorithm; Grey model; Health state; Oil-filled pressure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2011 International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4244-8162-0
  • Type

    conf

  • DOI
    10.1109/ICECENG.2011.6057830
  • Filename
    6057830