Study on damage identification of High-Speed railway truss bridge based on statistical steady-state strain characteristic function

The localization and quantification of damage in bridge structures have always been a challenging problem, especially for high-speed railway truss bridges with intricate structural forms and complex load conditions. To address this issue, this paper proposes a novel damage indicator based on strain characteristic functions, and integrated it into an automated framework for real-time damage detection which is particularly suitable for inservice structural health monitoring applications. To evaluate the effectiveness of this approach, a study is conducted using a finite element digital twin model to simulate the structural responses at critical areas of highspeed railway truss bridges under train-induced loads. The proposed damage indicator of the model was used to investigate and evaluate different types of bridge damage, reflecting both the location and severity of damage in high-speed railway truss bridges. The results suggest that the proposed damage indicator, when used with a distributed sensor system, shows promise in accurately locating and measuring damage in high-speed railway truss bridges. In addition, for the bridge health monitoring system with sparse sensor distribution, this indicator can provide a probability assessment of various damage conditions of a high-speed railway truss bridge. This information could potentially assist in the process of conducting in-service maintenance of a high-speed railway truss bridge.