Damage detection of highway bridges based on long-gauge strain response under stochastic traffic flow

Abstract

Abstract Highway bridges are essential infrastructure engineering. To monitor their conditions effectively, bridge structural health monitoring (SHM) techniques have been developed to substitute the manual inspection. Among SHM techniques, the damage detection method is the most promising one utilized for identifying damage location and extent. However, most frequency-domain signal based damage detection methods are not sufficiently sensitive to local damage, while other time-domain signal based methods with a sufficient sensitivity have many limitations, especially on working conditions where those methods are only feasible when just a single vehicle passes over the bridge. This restriction severely differs with actual traffic situations. Under these backgrounds, in this study, a damage detection method based on long-gauge fibre Bragg grating (FBG) was proposed, which can achieve the identification of the damage location and extent under stochastic traffic flow. This method’s feasibility was initially verified through a series of indoor bridge model experiments. Then, some numerical case studies were conducted to mimic actual stochastic traffic flow conditions. The results of experiment and numerical simulation demonstrated that this method performs well in detecting the damage location and extent under various designed situations, and it has the potential to be an alternative for the current methods.