Vision-based multi-point real-time monitoring of dynamic displacement of large-span cable-stayed bridges

The existing vision measurement methods face a significant challenge in the multi-point displacement monitoring of large-span bridges due to the contradiction between the measurement scale and image spatial resolution. Based on a cable-stayed bridge on a kilometer scale, a new vision-based multi-point displacement monitoring system is proposed. The bridge was designed and arranged with a camera network, consisting of a series of double-head camera stations that were connected by cooperative markers. Based on the observed multi-point deflection and lateral displacement, the deformation evolution of the bridge in the two dimensions of time and space is discussed. The results show that the proposed vision-based camera network can accurately monitor the dynamic deflection and lateral displacement across the whole span of the bridge. The measurement errors induced by the camera motion can be well compensated based on the optical constraints of the proposed camera network. The feasibility of the vision method for long-span bridge monitoring has greatly improved. The proposed system can provide a new method for displacement monitoring and fine parameters for the safety evaluation of large-span bridges.