###### Abstract  
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. vehicle-bridge coupling; continuous wavelet transform; vehicle scanning method; variational mode decomposition; structural health monitoring [PERSON], [PERSON], [PERSON], and [PERSON] 2025  
11 Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology,  
Kunming 650500, China  
1 Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology,  
Kunming 650500, China  
11 Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology,  
Kunming 650500, China  
and lowers costs, which hold significant engineering and economic importance. Bridge damage detection methods can be classified as direct or indirect. Direct detection methods typically involve deploying sensors (such as accelerometers, strain gauges, or fiber optic sensors) on bridges to collect vibration, strain, or displacement data and then evaluating the structural damage [1; 2; 3; 4]. Direct detection methods often require short-term traffic closures to ensure data quality. However, long-term real-time monitoring systems (such as wireless sensor networks), developed in recent years, can continuously collect data during normal bridge operation without disrupting traffic. They necessitate the deployment of numerous sensors, resulting in high detection costs. Therefore, structural health monitoring (SHM) systems, as outlined in [5], are predominantly implemented for long-span bridges, repairs for which typically have greater financial resources compared with those for their short- or medium-span counterparts. To address the shortcomings of direct detection approaches, researchers have introduced indirect methods for assessing structural damage in bridges. These techniques estimate the condition of the structure by analyzing its dynamic responses to external excitations--such as vehicular traffic or wind--and integrating numerical modeling with advanced signal processing algorithms. The vehicle scanning approach represents an indirect detection technique, wherein the bridge's structural condition is inferred by analyzing the dynamic responses of the vehicles traversing it. Compared with traditional direct detection methods, vehicle scanning methods have the following advantages: they do not require traffic closures, have minimal impact on normal bridge use during detection, can provide comprehensive monitoring of the entire bridge, offer overall damage assessment, and provide early damage warning, enhancing the timeliness and effectiveness of detection.