Transfer Reconstruction from High-Frequency to Low-Frequency Bridge Responses Under Vehicular Loading with a ResNet

Abstract

The reconstruction of bridge responses has been a significant area of focus within the field of structural health monitoring. This process entails the cross-reconstruction of responses from various cross-sections to identify any anomalies at specific locations, which may indicate the presence of structural defects. Traditional research has concentrated on simulating the relationships between different cross-sections for both high- and low-frequency components in isolation. However, this study introduces an innovative approach using a residual network (ResNet) to reconstruct high-frequency bridge responses under vehicular loading and demonstrates its applicability to low-frequency response reconstruction as well. The theoretical basis of this method is established through an analysis of the dynamics within a simplified vehicle-bridge-interaction (VBI) system. This analysis reveals that the transfer matrices for both high- and low-frequency components remain consistent across various loading conditions. Then, a data interception technique is introduced to separate high-frequency, low-frequency, and temperature-related components based on their spectral characteristics. The ResNet modeled the inter-sectional relationships of the high-frequency components and was then used to reconstruct the low-frequency responses under vehicular loading. The methodology was validated using a series of finite element models, confirming the uniformity of the transfer matrix between high- and low-frequency vibration components of the bridge. Field testing was also conducted to evaluate the practical effectiveness of the method. The proposed transfer–reconstruction method is expected to significantly reduce training dataset requirements compared with existing methods, thereby enhancing the efficiency of structural health monitoring systems.