• DocumentCode
    3031306
  • Title

    An improved method of structural random loading identification

  • Author

    Xianren, Kong ; Jun, Liao ; Dafu, Xu

  • Author_Institution
    Res. Center of Satellite Technol., Harbin Inst. of Technol., Harbin, China
  • fYear
    2010
  • fDate
    8-10 June 2010
  • Firstpage
    343
  • Lastpage
    346
  • Abstract
    Random loading identification has long been a difficult problem for multi-input-multi-output stationary random vibration problems. In this paper, the inverse pseudo-excitation method is used for dealing with such identification problems, and condition number weighted average method is developed to improve the rank defect of the frequency response function matrix during the process of random loading identification; simulation process is given to compare the result between the presented method and routine method. It proves the optimizing result by use of the method; experiments are designed to certify the feasibility of the algorithm, and achieve good results, and the ill-conditioning problem can be conquered to some extent. The condition number of FRF is used to choose the response measuring point, it reduces the workload, and get a accurate result.
  • Keywords
    condition monitoring; frequency response; inverse problems; matrix algebra; structural engineering; vibrations; condition number weighted average method; frequency response function matrix; ill conditioning problem; inverse pseudoexcitation method; multiinput multioutput stationary random vibration problems; structural random loading identification; Algorithm design and analysis; Frequency response; Load modeling; Loading; Matrices; Noise; Vibrations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Control in Aeronautics and Astronautics (ISSCAA), 2010 3rd International Symposium on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-6043-4
  • Electronic_ISBN
    978-1-4244-7505-6
  • Type

    conf

  • DOI
    10.1109/ISSCAA.2010.5632495
  • Filename
    5632495