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<p>The residual contact responses (RCP) of a two-axle vehicle are exploited to extract the modal frequencies of damped thin-walled box bridges with road roughness in this study. This approach eliminates the need for multiple connected vehicles and their consistent operation conditions, and the masking effect of vehicle frequencies is effectively removed. To start with, an analytical solution for the RCP is derived to identify the dominant frequencies included in it. Subsequently, a finite element model of a three-dimensional vehicle-bridge interaction is established for numerical analyses. Finally, the effects of road roughness, vehicle speeds, vehicle eccentricities, bridge damping and environmental noise on bridge frequency identification are studied. Investigations reveal that the first few vertical and flexural–torsional frequencies of the bridge are successfully extracted from the RCP. Moreover, RCP-based bridge frequency identification demonstrates strong robustness against environmental noise. The excellent performance in the bridge frequency identification is achieved at a vehicle speed of 8&#xa0;m/s and an eccentricity of 2&#xa0;m.</p>

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Extraction of vertical and flexural–torsional frequencies of thin-walled box bridges with road roughness and damping from the residual contact response of a two-axle vehicle

  • 期刊论文

  • 发表日期：

    2025年10月14日

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  • Yong Cai,
  • Qiqi Feng,
  • Liupeng Li,
  • Xueqi Li

摘要

The residual contact responses (RCP) of a two-axle vehicle are exploited to extract the modal frequencies of damped thin-walled box bridges with road roughness in this study. This approach eliminates the need for multiple connected vehicles and their consistent operation conditions, and the masking effect of vehicle frequencies is effectively removed. To start with, an analytical solution for the RCP is derived to identify the dominant frequencies included in it. Subsequently, a finite element model of a three-dimensional vehicle-bridge interaction is established for numerical analyses. Finally, the effects of road roughness, vehicle speeds, vehicle eccentricities, bridge damping and environmental noise on bridge frequency identification are studied. Investigations reveal that the first few vertical and flexural–torsional frequencies of the bridge are successfully extracted from the RCP. Moreover, RCP-based bridge frequency identification demonstrates strong robustness against environmental noise. The excellent performance in the bridge frequency identification is achieved at a vehicle speed of 8 m/s and an eccentricity of 2 m.