Vision-based identification of cable tensions and finite element model verification of a cable-stayed bridge

The utilization of cables as primary load-bearing elements in structures is increasing due to advancements in material properties, analysis techniques, and construction processes. The estimation of the cable tensions with the Structural Health Monitoring (SHM) systems is necessary to ensure operational and structural safety and integrity. Fatigue caused by cyclic traffic and wind loads, corrosion due to environmental factors, and sudden earthquake loads cause a change in cable tensions, which affects the overall performance of the structure. In this study, it is aimed to estimate the cable tensions of the Komurhan cable-stayed bridge using a vision-based modal identification. Cable tensions are determined using the lift-off test and estimated using the vibration response from eight data sets recorded by the existing acceleration sensors on the bridge. Then, cable tensions are estimated by vision-based methods using video recordings. In the first two methods, only 8 of 42 cables are continuously monitored; on the other hand, all cable tensions are estimated with the vision-based identification and give consistent results with the existing monitoring system. In the last part of the study, finite element model (FEM) is developed, and the cable tensions in the model are changed based on all cable tensions from the vision-based identification. Additionally, the natural frequencies of the pylon and deck in the FEM correspond with those from the vibration records of eight data sets, thereby verifying the FEM. The consistency of the natural frequencies further confirms the accuracy of the defined cable tensions in the model.