Long-Term Real-Time Monitoring of Suspension Bridge Hangers Using Vision-Based Systems

This paper describes the findings and conclusions from a long-term monitoring campaign where the Digital Image Correlation (DIC) technique was used to gather data on wind- and traffic-induced displacements of the longest hangers of the Great Belt Suspension Bridge. The paper highlights the benefits and limitations of vision-based technology. The monitoring outcome provided previously inaccessible information on dynamic behavior of the hangers and structural movements of the bridge deck and informed next steps with respect to the fatigue management. The results show good agreement (92% correlation) between the data collected using the DIC system and the measurements from the accelerometer sensors. The DIC system allowed high-precision measurements (±1 mm precision from approximately 100 m) and enabled visual data verification of the results. Furthermore, traffic load monitoring data captured can be used to verify how many (potentially overloaded) vehicles cross the bridge per month. Vision-based techniques can be deployed on other long-span cable-supported bridges, enabling real-time evaluation of the dynamic monitoring data and cost-efficient identification of problems in hanger functioning. To the author’s knowledge, this is the first study to use the DIC technique for continuous monitoring of suspension bridge hangers.