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Moving Load Identification with Long Gauge Fiber Optic Strain Sensing

Author(s): ORCID (School of Civil Engineering, Sichuan Agricultural University, Dujiangyan 611830, China)
ORCID (Jiangsu Key Laboratory of Engineering Mechanics, Southeast University, Nanjing 210096, China)
ORCID (Jiangsu Key Laboratory of Engineering Mechanics, Southeast University, Nanjing 210096, China)
Medium: journal article
Language(s): English
Published in: The Baltic Journal of Road and Bridge Engineering, , n. 3, v. 16
Page(s): 131-158
DOI: 10.7250/bjrbe.2021-16.535
Abstract:

Moving load identification has been researched with regard to the analysis of structural responses, taking into consideration that the structural responses would be affected by the axle parameters, which in its turn would complicate obtaining the values of moving vehicle loads. In this research, a method that identifies the loads of moving vehicles using the modified maximum strain value considering the long-gauge fiber optic strain responses is proposed. The method is based on the assumption that the modified maximum strain value caused only by the axle loads may be easily used to identify the load of moving vehicles by eliminating the influence of these axle parameters from the peak value, which is not limited to a specific type of bridges and can be applied in conditions, where there are multiple moving vehicles on the bridge. Numerical simulations demonstrate that the gross vehicle weights (GVWs) and axle weights are estimated with high accuracy under complex vehicle loads. The effectiveness of the proposed method was verified through field testing of a continuous girder bridge. The identified axle weights and gross vehicle weights are comparable with the static measurements obtained by the static weighing.

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: 10.7250/bjrbe.2021-16.535.
  • About this
    data sheet
  • Reference-ID
    10768554
  • Published on:
    24/04/2024
  • Last updated on:
    24/04/2024
 
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