Study on strain characteristic function for performance evaluation of high-speed railway steel truss bridge

Abstract

From the data collected by bridge health monitoring systems, various indicators can be derived to evaluate the structural, environmental, and loading conditions. These indicators provide a basis for decision-making of bridge operations managers and administrators. In this paper, a new monitoring indicator called the Statistical Steady-State Static Effect Characteristic Function is proposed for railway bridges. A digital twin (DT) finite element model is developed in this study, which allows for real-time analysis of the structural effects during train travel. Using this model, the strain effects on key components of a high-speed railway steel truss bridge under dynamic loading conditions caused by random trains are simulated. Based on the characteristics of the simulation results, an extraction algorithm for the statistical steady-state strain characteristic function of the high-speed railway steel truss bridge is proposed in this study. By simulating the strain effects under multiple random train travel events, the strain characteristic functions at different locations of the structure are extracted, demonstrating the applicability of the proposed algorithm. Finally, by comparing these strain characteristic functions, the distribution pattern in the structural configuration space is revealed, suggesting the potential of the function as an indicator for assessing inherent structural characteristics, monitoring structural condition, and identifying damage.