• DocumentCode
    2562780
  • Title

    The method of the aerocraft health diagnosis based on chaos theory

  • Author

    Cui, Jianguo ; Xu, Xinhe ; Li, Zhonghai ; Zhang, Daqian ; Cai, Weimin ; Li, Guangyao

  • Author_Institution
    Automatization Coll., Shenyang Inst. of Aeronaut. Eng., Shenyang
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    2712
  • Lastpage
    2715
  • Abstract
    To diagnose effectively the aerocraft key structure components fatigue damages, discover in good time hidden trouble, avoid fearful accident occurring, the advanced acoustic emission (AE) technology is used to monitor the aerocraft stabilizer health state and get the AE information. Chaos theory is used to extract the correlation dimension of the AE information and construct the character vector. And the health diagnosis arithmetic is designed to diagnose the health state of the aerocraft stabilizer by fuzzy Kohonen clustering network. A new kind of fatigue damage health diagnosis approach to the aerocraft stabilizer, based on AE information correlation dimension and fuzzy Kohonen clustering network, is proposed in this paper. Experiments show that the approach has good performance to diagnose the fatigue crack of the aerocraft stabilizer. It presents a new approach to diagnose effectively health state of aircraft structure components.
  • Keywords
    aircraft control; aircraft maintenance; chaos; fatigue cracks; fault diagnosis; fuzzy systems; advanced acoustic emission; aerocraft health diagnosis arithmetic; aerocraft key structure components; aerocraft stabilizer; aircraft structure component health state; chaos theory; fatigue crack diagnosis; fatigue damage health diagnosis; fuzzy Kohonen clustering network; Chaos; Aerocraft Stabilizer; Correlation Dimension; Fuzzy Clustering Network; Health Diagnosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4597819
  • Filename
    4597819