Fully automated modal tracking for long-span high-speed railway bridges
Xiao‐Mei Yang, Hong‐Nan Li, Ting‐Hua Yi, Chunxu Qu, Hua Liu
Abstract
Modal parameters are inherent structural characteristics that are valuable for model updating, condition assessment, and early warning of bridges. Operational modal tracking technology has been a popular research topic in bridge structural health monitoring (SHM) because of its output-only advantage; that is, only the vibration responses of the bridge are necessary for modal identification. The real-time objective of bridge SHM requires operational modal tracking to be fully automated. Because the loads acting on long-span high-speed railway bridges are various, the modal identification methods should be changed according to the excitation characteristics; otherwise, the results may be incorrect. However, there is no unified framework for simultaneously tracking the modal evolution of a bridge under different excitations. In this study, modal tracking strategies based on ambient loads, train loads and immediately a train moving past the bridge were developed to identify the operational modal parameters of the bridge. In addition, a unified tracking framework was established to automatically switch among the three-stage modal-tracking strategies, which utilizes the real-time positioning of the axle loads. Furthermore, the computational efficiency of the tracking strategies and the obstacles of operational modal analysis were analyzed to provide a reference for mode-based SHM of bridges, and the essential parameters in the tracking algorithms were suggested. The three-stage modal-tracking methods were validated through long-term monitoring data of a long-span high-speed railway bridge. The results indicated that the best tracking results were generated from free-vibration data, while the modal-tracking under ambient loads had best timeliness.