Abstract
The vibration response of a damaged bridge is known to have changed characteristics. To analyze the response, we start by collecting waveforms of the vibration immediately following the passage of a vehicle. We then need to isolate just those vibrations caused by a single heavy vehicle, if the vibration characteristics are to be accurate. In this paper, we propose a traffic-vibration analysis system that interacts with a surveillance camera. The system identifies a vehicle from the video by combining a moving-object detector with a neural-network-based object detector, thereby estimating automatically the bridge's natural frequencies and damping ratios as features that characterize the bridge's damage.