The vehicle scanning method (VSM) is widely used for bridge damage identification (BDI) because it relies solely on vehicle dynamic responses. The recently introduced contact point response, which is derived from vehicle dynamics but devoid of vehicle-related natural frequencies, shows great potential for application in the vehicle scanning method. However, its application in bridge damage detection remains understudied. The aim of this paper is to propose a new bridge damage identification method based on the contact point response. The method uses variational modal decomposition (VMD) to solve the problem of mode mixing and spurious frequencies in the signal. The continuous wavelet transform (CWT) is then utilized for damage identification. The introduction of variational modal decomposition makes the extracted signal more accurate, thus enabling more accurate damage identification. Numerical simulations validate the method’s robustness under varying conditions, including the vehicle speed, wavelet scale factors, the number of bridge spans, and pavement roughness. The results demonstrate that variational modal decomposition eliminates signal artifacts, producing smooth variational modal decomposition–continuous wavelet transform curves for accurate damage detection. In this study, we offer a robust and practical solution for bridge health monitoring using the vehicle scanning method.

Using a two-axle test vehicle, a new drive-by-based bridge damage identification method is proposed in this study. The method firstly obtains the vehicle acceleration response of a vehicle passing through an undamaged bridge and a damaged bridge; then, the acceleration response is processed using successive variational modal decomposition (SVMD) to obtain the intrinsic modal function (IMF) corresponding to the driving frequency; finally, the difference of the IMF is used to construct a damage indicator for damage identification of the bridge. The main findings of this study are as follows: (1) the constructed damage index can successfully identify single and multiple damages of bridges; (2) even in the case of pavement roughness, the proposed damage index is still able to identify the location of the damage; (3) the constructed damage index is not only applicable to simply supported bridges, but also applicable to the damage identification of continuous bridges; (4) the experiment shows that the proposed damage index can successfully identify the damage location, but the local vibration of the vehicle and the measurement noise interfere with the damage identification effect severely.