Model Updating of Railway Bridge Using In Situ Dynamic Displacement Measurement under Trainloads

Abstract

To address the need for monitoring aging railway bridges, this paper presents a finite-element (FE) model updating approach using time-domain optimization based on in situ measurement of the bridge’s dynamic displacement histories under trainloads. Field tests are performed on a short-span plate girder railway bridge to measure its displacement response to freight trainloads with different speeds using a low-cost remote vision sensor recently developed by the authors’ group. A FE model of the bridge is developed considering train–track–bridge dynamic interactions. Sensitivity analysis is carried out to investigate the intrinsic effects of parameters of the train, track, and bridge subsystems on the dynamic response of the bridge. It is found that the bridge displacement response is primarily sensitive to the stiffness of the bridge, whereas the acceleration response is affected by many other parameters. This justifies that the bridge dynamic displacement is more suited than acceleration for updating the railway bridge stiffness. Consequently, a model updating approach is proposed using the measurement of bridge displacement response to trainloads. This approach is applied to the short-span bridge to first identify the train speed, followed by the bridge stiffness by minimizing the error between the measured and computed displacement time histories. Furthermore, this paper investigates the frequency characteristics from both the measured and computed displacements. The analysis shows that the trainload does not excite the bridge’s natural modes of vibration because the frequency is much lower than the bridge’s natural frequencies. Therefore, it is difficult to use the modal identification-based FE model updating methods based on the dynamic response measurement. This is commonly the case for short-span railway bridges, which tend to have high natural frequencies. The proposed periodic displacement measurement and time-domain FE model updating can be developed into an effective tool for long-term structural health monitoring of short-span railway bridges.