Smart Structures and Systems

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Time-varying characteristics analysis of vehicle-bridge interaction system using an accurate time-frequency method

  • Tian-Li Huang (School of Civil Engineering, Central South University) ;
  • Lei Tang (School of Civil Engineering, Central South University) ;
  • Chen-Lu Zhan (School of Civil Engineering, Central South University) ;
  • Xu-Qiang Shang (School of Civil Engineering, Central South University) ;
  • Ning-Bo Wang (School of Civil Engineering, Central South University) ;
  • Wei-Xin Ren (College of Civil and Transportation Engineering, Shenzhen University)
  • Received : 2023.07.10
  • Accepted : 2024.01.10
  • Published : 2024.02.25
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Abstract

The evaluation of dynamic characteristics of bridges under operational traffic loads is a crucial aspect of bridge structural health monitoring. In the vehicle-bridge interaction (VBI) system, the vibration responses of bridge exhibit time-varying characteristics. To address this issue, an accurate time-frequency analysis method that combines the autoregressive power spectrum based empirical wavelet transform (AR-EWT) and local maximum synchrosqueezing transform (LMSST) is proposed to identify the time-varying instantaneous frequencies (IFs) of the bridge in the VBI system. The AR-EWT method decomposes the vibration response of the bridge into mono-component signals. Then, LMSST is employed to identify the IFs of each mono-component signal. The AR-EWT combined with the LMSST method (AR-EWT+LMSST) can resolve the problem that LMSST cannot effectively identify the multi-component signals with weak amplitude components. The proposed AR-EWT+LMSST method is compared with some advanced time-frequency analysis techniques such as synchrosqueezing transform (SST), synchroextracting transform (SET), and LMSST. The results demonstrate that the proposed AR-EWT+LMSST method can improve the accuracy of identified IFs. The effectiveness and applicability of the proposed method are validated through a multi-component signal, a VBI numerical model with a four-degree-of-freedom half-car, and a VBI model experiment. The effect of vehicle characteristics, vehicle speed, and road surface roughness on the identified IFs of bridge are investigated.

Keywords

Acknowledgement

The authors are grateful for the financial support from the National Natural Science Foundation of China (Grant Nos. 52078486 and 52278233), the National Key Research and Development Program of China (Grant No. 2021YFE0105600), the Key Project for Scientific and Technological Cooperation Scheme of Jiangxi Province (Grant Nos. 20212BDH80022 and 20223BBH80002).

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