Real time monitoring and evaluation of overturning risk of single-column-pier box-girder bridges based on identification of spatial distribution of moving loads

Abstract The evaluation of the overturning risk of the main girder of single-column-pier box-girder bridges has always been one of the focuses of safety monitoring during the service period of this kind of bridge. The bridge health monitoring technology can provide important data support and offer effective analytical tools for solving this problem. By monitoring the displacement and inclination of the bearing section, although the real time assessment of the overturning risk of the main girder can be achieved, it falls short in their ability to predict the overturning risk in advance. Therefore, a real time monitoring method for the overturning risk of box-girder bridges with predictive ability is proposed in this paper. This method combines machine vision and weigh-in-motion monitoring information to identify the real time distribution of the actual vehicle queue within the specified area of the bridge deck. Furthermore, the analytical expression of the support reaction of the main girder is derived to realize the real time calculation of the support reaction. Based on this, a method is developed to evaluate the overturning risk of the bridge within the monitored region in real time, and by using the measured vehicle trajectories, to predict the overturning risk of the adjacent bridges in front. The effectiveness of the proposed method is verified through both the field data and finite element model of a straight single-column-pier bridge.