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Moving Load Identification of Small and Medium-Sized Bridges Based on Distributed Optical Fiber Sensing

Author(s):





Medium: journal article
Language(s): English
Published in: International Journal of Structural Stability and Dynamics, , n. 4, v. 16
Page(s): 1640021
DOI: 10.1142/s0219455416400216
Abstract:

A novel method was proposed for the moving load identification of bridges based on the influence line theory and distributed optical fiber sensing technique. The method of load and vehicle speed identification was firstly theoretically studied, and then numerical simulation was also performed to study its accuracy and robustness. The numerical results showed that this method was characterized by high accuracy and excellent resistance to noise. Finally, the load identification of an actual continuous pre-stressed concrete beam bridge was carried out with the proposed method. The bridge consists of four pre-stressed box beams. At the same time, a weigh-in-motion system was also installed about 200 m in front of the bridge to measure the speed and moving loads with a purpose of comparing the load identification of the proposed method. Long gauge fiber Bragg grating (FBG) sensors with a gauge length of 1.0 m were adhered to the bottom of the beams. The individual loaded vehicles and the corresponding structure response were mainly monitored as standard samples, and the speed and weight of the sample vehicles were monitored and identified with the proposed method. The results revealed that the distributed long gauge FBG sensors were capable of sensing the structure response precisely and identifying the traffic load. On the basis of the design information and ambient vibration testing results, a refined model was established and the response under unit moving load was acquired for load identification. It was also shown that the sensors in different positions can achieve accurate vehicle speed and weight, the relative error of which are within 10% and 15%, respectively.

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/s0219455416400216.
  • About this
    data sheet
  • Reference-ID
    10352543
  • Published on:
    14/08/2019
  • Last updated on:
    14/08/2019