Photogrammetric monitoring of load-induced vertical deformations in the superstructure of a research bridge

Abstract

Abstract. Structural health monitoring of bridge infrastructure is conventionally carried out either through the acquisition of data from embedded sensor arrays or through systematic inspection and documentation of surface-observable changes on the structure. External deterioration, such as crack formation or load-induced structural deformations, is typically identified during these inspections. However, conventional visual inspections are often labor-intensive and costly. Automated, camera-based photogrammetric monitoring methods offer a promising alternative to reduce both effort and expense. For the specific task of detecting vertical deformations in a bridge superstructure, a tripod-stabilized mono camera setup can be utilized. This approach enables the derivation of vertical deformations by tracking the displacement of target points within a predefined measurement field over time. This study investigates the derivation of vertical deformations from image sequences. Using a representative test bridge as a case study, the characteristic vertical deformation response induced by the traversal of a loaded vehicle is analyzed and documented. A measurement point field was affixed to the bridge superstructure and continuously observed. From the acquired image sequences, continuous vertical displacements were successfully derived, with a mean vertical deflection of the bridge superstructure in the range of −1.71 mm to +0.72 mm. The mean measurement noise, averaged across all monitored test cycles, amounted to 0.01 mm. The results demonstrate that high-quality deformation data can be acquired in a cost-efficient manner using a consumer-grade camera in conjunction with a standardized measurement field, thereby offering a viable low-cost alternative to conventional structural monitoring instrumentation.