Influence Line-Based Damage Detection Technique for Long-Span Bridges

Abstract

Numerous long-span cable-supported bridges have been built throughout the world in recent years. These bridges begin to deteriorate once built and continuously accumulate damage during their long service life. The growing popularity of comprehensive structural health monitoring systems (SHMS) in recently built longspan bridges has started a new trend of integrating SHMS and damage detection technology for real-time condition assessment of these bridges. This paper explores a novel damage detection technique based on stress influence lines (SILs) of bridge components, and validates the efficacy of the technique through a case study of the Tsing Ma Suspension Bridge. A mathematical regularization method is first introduced to identify SILs based on the in situ measurement of train information and train-induced stress responses in local bridge components. The first-order difference of SIL change is subsequently proposed as a damage index and applied to hypothetical damage scenarios. The comparison indicates that it is an accurate indicator of the damage location. Thus, the proposed SIL-based method offers a promising real-time technique for damage location in long-span bridges with comprehensive SHMS.