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Using theoretical modeling combined with monitoring data, the typical dynamic and static behaviors of a continuous steel truss arch railway bridge are evaluated. The dynamic behavior involves an impact factor induced by the action of running trains, and the static behavior refers to axial bending performance and the stress distribution among different planes of the truss. The transverse position, length, and speed of running trains are introduced to conduct an analysis of their influences on the dynamic and static behaviors of the bridge superstructure. A structural safety evaluation is also conducted by comparison with the provisions recommended by design codes and by analysis of absolute stress. It is concluded that three types of members present different dynamic behaviors and that the value of the impact factor for chords B exceeds the provision recommended by the design codes. Chords C present the greatest ratio of bending stress versus axial stress. An imbalance of stress distribution exists among the three planes of the truss, and the difference is the smallest when trains run along the middle railways. Because the train-induced stress is considerably lower, the dynamic and static performances of the bridge are within the scope of safety.

Nanjing Dashengguan Bridge, which serves as the shared corridor crossing Yangtze River for both Beijing-Shanghai high-speed railway and Shanghai-Wuhan-Chengdu railway, is the first 6-track high-speed railway bridge with the longest span throughout the world. In order to ensure safety and detect the performance deterioration during the long-time service of the bridge, a Structural Health Monitoring (SHM) system has been implemented on this bridge by the application of modern techniques in sensing, testing, computing, and network communication. The SHM system includes various sensors as well as corresponding data acquisition and transmission equipment for automatic data collection. Furthermore, an evaluation system of structural safety has been developed for the real-time condition assessment of this bridge. The mathematical correlation models describing the overall structural behavior of the bridge can be obtained with the support of the health monitoring system, which includes cross-correlation models for accelerations, correlation models between temperature and static strains of steel truss arch, and correlation models between temperature and longitudinal displacements of piers. Some evaluation results using the mean value control chart based on mathematical correlation models are presented in this paper to show the effectiveness of this SHM system in detecting the bridge’s abnormal behaviors under the varying environmental conditions such as high-speed trains and environmental temperature.

Making use of long-term transverse vibration monitoring data of DaShengGuan Bridge, the early-warning method of train running safety of the high-speed railway bridge is established by adopting principal component analysis (PCA) method. Firstly, the root mean square (RMS) of the transverse acceleration of the main girder is used as the monitoring parameter for the train running safety. The correlation model between the RMS values measured from different positions is further adopted as the evaluating model for the train running safety. Finally, the effects of the environmental changes on the evaluating model are eliminated using the PCA method and the warning index for the train running safety is further constructed. The analysis results show that the correlation between the RMS values of the accelerations from different measuring positions on the main girder can be analyzed by a quadratic polynomial fitting model. The PCA method can effectively remove the environmental effects on the quadratic polynomial fitting model. The proposed warning method provides a good capability for detecting the abnormal changes of the measured transverse accelerations and hence it is suitable for early-warning of the train running safety.