With the goal of safety monitoring of large-scale infrastructure structures,Systematically sort out the indicators that affect structural safety, establish a system for monitoring structural safety based on key indicators, an overall plan for massive real-time data acquisition and transmission of large-scale infrastructure structure safety monitoring systems was designed, and the data flow of each monitoring item of the system was sorted out, proposed a real-time data collection strategy and overall architecture.By mining, cleaning, and preprocessing heterogeneous data from multiple sources, high-quality data storage can be achieved, which not only effectively realized the shared use and centralized management of data collected by infrastructure monitoring systems in various places, but also provided experience for the later data analysis of large-scale infrastructure structure monitoring systems support.

This study aims to enhance the understanding of the state of large-scale bridge structures by accurately analyzing the structural changes of bridges through extensive real-time monitoring data. By conducting a comparative analysis of field load test data and simulation calculations of linear models, this research seeks to provide a precise assessment of structural indices, identify potential risks, and develop appropriate preventive measures. Using a domestic long-span suspension bridge as a case study, the bridge beam is conceptualized as a multi-degree-of-freedom structure, allowing for the application of linear structural vibration mode decomposition methods. During the on-site load testing, a structural health monitoring system is employed to collect real-time data, which facilitates the calculation of deflection and strain values for each control section under static load conditions. Additionally, the frequency response function, unit pulse response function, and covariance-related functions are utilized to derive the modal parameters of the structure during dynamic load testing. The health monitoring system’s measurements of strain, deflection, and modal parameters are then compared with the analytical results from the tests, while also verifying the operational integrity of the monitoring system. By referencing the assessment methodology for site load tests, this research analyzes the data mining from health monitoring systems to evaluate the bridge’s load-bearing capacity during testing, as well as for subsequent evaluations of the bridge’s structural health and operational status. The experimental findings demonstrate that the load testing equipment and health monitoring system effectively capture significant vehicle loading and unloading events. Furthermore, the analysis of the acquired vibration data yields reliable modal parameters, with deflection calibration coefficients and relative residual coefficients meeting established criteria. The calculated frequencies are found to exceed the theoretically predicted values, indicating that the global stiffness of the structure aligns with design specifications and that the mechanical properties comply with regulatory standards. This reflects the feasibility and effectiveness of the monitoring-based evaluation index system and methodology employed in this study.