Direct Structural Response Monitoring Versus Weight-Based Damage Detection in Bridge Weigh-in-Motion

Bridge weigh-in-motion (BWIM) systems estimate axle and gross vehicle weights from measured bridge responses, typically strains but also displacements and rotations, via algorithms based on influence lines. Changes in inferred weights have been proposed as damage indicators, allowing existing BWIM installations to contribute to structural health monitoring without additional sensors. However, BWIM accuracy is sensitive to discrepancies between idealised models and actual bridge–traffic conditions, including variability in vehicle configurations, road profiles, measurement noise, multiple-vehicle presence, and uncertainty in vehicle positioning. This paper uses a numerical vehicle–bridge interaction framework to compare the sensitivity of direct structural responses and BWIM-derived gross vehicle weights to global, local, and combined stiffness reductions in a short-span, simply supported bridge. The analysis considers different signal-to-noise ratios and field-representative BWIM error distributions corresponding to COST 323 accuracy classes. Direct monitoring of strain, displacement, and especially rotation provides slightly higher sensitivity to global stiffness changes than BWIM-inferred weights, but BWIM-inferred weights derived from rotations can be more robust than direct responses for detecting local damage under low signal-to-noise ratios. When BWIM calibration and modelling errors are included, detection performance degrades rapidly with decreasing accuracy class; meaningful local-damage detection is achieved only for the highest class. Multi-sensor configurations combining strain and rotation help distinguish quasi-uniform global changes from localised damage by exploiting their differential sensitivity to global and local stiffness variations.