We propose a method for load rating of prestressed box beam (PSBB) bridges based on their dynamic response collected
using wireless sensor networks (WSNs). The hypothesis includes that the health of a bridge is associated with its
vibration signatures. We deployed two WSNs on a 25-year old PSBB bridge, and ran trucks with variable loads and
speeds for collecting its real-time dynamic response at current condition. We also performed FE simulations of 3-D
bridge models under vehicular loads to acquire the representative dynamic response at its newest condition. We validated
the bridge model by field testing and numerical analysis. We used Fast Fourier Transform and peak-picking algorithms
to find maximum peak amplitudes and their corresponding frequencies. We calculated the in-service stiffness of the
bridge to determine its load rating, which resembles the actual load rating of the bridge. The application software
developed from this research can instantly determine the load rating of a PSBB bridge by collecting its real-time
dynamic response. The research outcome will help reduce bridge maintenance costs and increase public safety.
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