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Identifying Mode Shapes of Girder Bridges Using Dynamic Responses Extracted from a Moving Vehicle Under Impact Excitation

Author(s):

Medium: journal article
Language(s): English
Published in: International Journal of Structural Stability and Dynamics, , n. 8, v. 17
Page(s): 1750081
DOI: 10.1142/s021945541750081x
Abstract:

The mode shapes of a bridge are important modal properties for many purposes, such as damage detection and model updating. Traditional methods for constructing mode shapes often require installation of instruments on the bridge for collection of dynamic responses. However, these methods are not only costly but also inconvenient. Therefore, a method is developed for constructing the mode shapes of girder bridges using the dynamic responses extracted from a moving vehicle under impact excitation. This paper reports some numerical simulations based on finite element modeling. First, the dynamic responses of a moving vehicle under impact excitation are generated for simulation. Then the component response associated with each natural frequency of the bridge is extracted by using a suitable filter. Finally, the mode shape associated with each natural frequency identified is constructed from the extracted component response and its Hilbert transform pair. The proposed method uses only the information measured from the moving vehicle, which acts both as a sensor and an exciter. Moreover, the additional impact excitation on the vehicle helps to excite the bridge. This helps to improve the accuracy by overcoming the adverse effects of measurement noise and road surface roughness. The effects of measurement noise, road surface roughness and vehicle speed on the accuracy of results are evaluated. A numerical study is presented to verify the feasibility of the proposed method.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1142/s021945541750081x.
  • About this
    data sheet
  • Reference-ID
    10352344
  • Published on:
    14/08/2019
  • Last updated on:
    14/08/2019
 
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