Fully automated modal tracking for long-span high-speed railway bridges

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.