Abstract

This paper proposed an indirect bridge frequency identification and damage detection method based on the virtual contact-point (CP) responses of railway vehicles moving over the bridge. The virtual CP response is acquired to reduce the inverse effects of the track irregularity and vehicle dynamic components on the indirect bridge monitoring of the vehicle–bridge interaction (VBI) system. By combining the virtual CP responses of multiple connected vehicles, the first three bridge frequencies can be identified when vehicles run at high speed. The synchrosqueezing transform (SST) is then adopted to extract bridge-related dynamic components from the virtual CP response for bridge modal identification. The time-frequency (TF) representation of the virtual CP response using SST is further analyzed for bridge damage detection. The spectral entropy (SE) of the TF representation is introduced to quantify TF changes and serves as a damage index for bridge damage localization. Numerical studies are conducted to investigate the effects of measurement noise, damage conditions, and track irregularity on the effectiveness of the proposed method. The results demonstrate that SE is a good indicator for damage detection, and that the proposed method combined with wavelet denoising has good anti-noise performance and can well locate bridge damage using virtual CP response.

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