Identification of Load-Relevant Train Motion Parameters Using Strain Monitoring Data of High-Speed Railway Bridges

The assessment of structural performance and service condition of high-speed railway (HSR) bridges is critical for meeting the lifecycle management requirements of HSR projects. To extract reliable structural information from bridge monitoring data, the identification of load-relevant parameters (e.g., train motion parameters) is essential. This paper proposes a method to identify load-relevant train motion parameters (i.e., number of carriages, direction of travel, traveling speed) during train crossing of HSR bridges, using structural strain monitoring data, with the dual goal of enabling accurate train load identification and supporting effective assessment of HSR bridge structural performance. An analytical model is established based on the dynamic strain response of the train-bridge interaction system during train passage. This model explicitly reveals the relationship between the waveform characteristics of structural strain time–history curves and the target train motion parameters. Building on this model, a set of algorithms for motion parameter identification is developed through systematic waveform analysis of structural strain monitoring data. The effectiveness and engineering applicability of the proposed method are validated using field monitoring data from an in-service HSR steel truss bridge. Results confirm that the identified parameters (number of carriages, travel direction, traveling speed) are consistent with the actual train operation status, verifying the method’s reliability for calibrating train load-related information and providing a practical tool for HSR bridge structural health monitoring.