Bridge scour damage detection using an instrumented in‐service vehicle

Abstract Drive‐by bridge health monitoring offers a promising, low‐cost approach for detecting subsurface damage using instrumented vehicles, reducing reliance on manual inspections and fixed structural sensors on individual structures. This study focuses on detecting scour damage, permanent settlement at bridge supports, using onboard measurements. A novel, self‐calibrating approach based solely on onboard measurements, is developed to estimate vehicle properties through an optimization process. With identified vehicle properties, the inverse Newmark‐Beta algorithm infers the profile and/or apparent profile, a combination of road surface profile and bridge deflection under the wheels. Scour damage is detected by observing changes in the inferred apparent profiles in healthy and damaged conditions. The approach is validated through simulations and field testing on a near‐full‐scale bridge at the European Commission's Joint Research Centre in Ispra, Italy. Simulations target the detection of 2 mm scour settlement, while the field testing successfully detects an average settlement of 4 mm over a number of runs. The results show a clear distinction in the apparent profile patterns between healthy and damaged states, with strong repeatability across multiple runs of the same vehicle. This demonstrates the method's reliability and potential for practical deployment in real‐world environments.