SSI-COV Performance Using Ambient Vibration Excitation and Free-Decays for Automatic OMA: An Application on a Reinforced Concrete Bridge

The deterioration of bridges, along with sustainability goals, demands improved SHM tools to enhance maintenance, complementing visual inspections. Direct SHM methods involve the deployment of sensors networks to extract quantitative information about bridge health under operational and environmental actions. Operational Modal Analysis (OMA) is a well-known technique in SHM, as it exploits the bridge’s response to operational inputs to effectively extract structure’s modal parameters, which indicate structural condition, being dependent on bridge’s mechanical properties. Automated OMA enables continuous monitoring of modal parameters, providing a clear assessment of bridge status over time. This study investigates the performance of an automated SSI-COV-based OMA, applied to a reinforced concrete railway bridge, analyzing the impact of different acceleration inputs on modal parameters identification. Two input types are considered: on one hand, a “canonical input”, representing bridge response to ambient excitation. On the other hand, the use of free decays automatically extracted after the passage of railway vehicles. The relevance of the analysis also lies in using acceleration data collected by a permanent monitoring system which is characterized by a reduced setup of dynamic sensors.