Stress influence line identification of long suspension bridges installed with structural health monitoring systems

Abstract

Numerous long-span suspension bridges have been built worldwide over the past few decades. To ensure the safety of such bridges and their users during the bridge service life, several bridges have been equipped with Structural Health Monitoring Systems (SHMSs), which measure dynamic bridge responses and various loading types on-site. Integrating SHMS and damage detection technology for condition assessment of these bridges has become a new development trend. Recent studies have proven that stress influence line (SIL)-based damage indices achieve excellent damage detection performance for a long suspension bridge. However, an accurate and prompt manner of identifying the SIL of a long suspension bridge is important to facilitate the development of the SIL for an effective damage index. Identifying the SIL from field measurement data under in-service conditions has several advantages over the traditional static loading test. This study proposes and develops a new SIL identification method by integrating the least squares solution and Weighted Moving Average (WMA) based on the measured train information and the corresponding train-induced stress time history. The efficacy of the proposed method is validated through its application to Tsing Ma Bridge (TMB). The good agreement between the identified and baseline SILs for a typical diagonal truss member verifies the effectiveness of the proposed method. Furthermore, robustness testing is performed by identifying SIL on the basis of information on different trains and train-induced stress responses and by identifying the SIL of different types of bridge components. Results indicate the feasibility of the application of the proposed approach to SIL identification for long-span bridges.