• DocumentCode
    508268
  • Title

    Identification of Flexural Rigidity and Tension of Short Hangers with Adding Mass and Neural Network

  • Author

    Xu, Xie ; Liangfeng, Sun ; Haiyan, Huang ; Jilong, Li

  • Author_Institution
    Dept. of Civil Eng., Zhejiang Univ., Hangzhou, China
  • Volume
    3
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    372
  • Lastpage
    376
  • Abstract
    The effect of flexural rigidity on natural frequency is great for short hangers. Hence, the flexural rigidity of hangers should also be identified besides the basic frequency in determination of hanger tension.Utilizing the significant effect of mass on natural frequency, the additional mass method (AMM) is proposed, with mass as an additional condition in the identification of hanger tension. According to the measured frequencies of hangers before and after the attachment of the mass., the flexural rigidity and tension of hangers can be estimated using Artificial Neural Network (ANN), which further solves the inverse calculation problem based on the nonlinear relationship among frequency, tension and stiffness. A group of short hangers with lengths in the range of 2-10 m are studied as the cases. Results show that the AMM is proved to be feasible in tension and flexural rigidity identification, and the ANN also gets validated in nonlinear inverse calculation.
  • Keywords
    bridges (structures); neurocontrollers; shear modulus; tensile strength; vibration control; additional mass method; artificial neural network; flexural rigidity identification; hanger tension determination; inverse calculation problem; short hangers; size 2 m to 10 m; Bridges; Cables; Force measurement; Frequency estimation; Frequency measurement; Magnetic flux; Neural networks; Time measurement; Transducers; Vibration measurement; neural network; short hanger; tension; vibration method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.320
  • Filename
    5366370