Short- and medium-span bridges form a substantial portion of transportation networks and are highly vulnerable to overload-induced damage, yet most existing weigh-in-motion (WIM) systems are unsuitable for these bridges due to their high cost and complex deployment. To address this challenge, this study proposes a bridge lightweight weigh-in-motion (LWIM) system that estimates vehicle weights using minimal instrumentation. By integrating mid-span visual deflection measurements, end-mounted acceleration signals, and short-term video campaigns, the system identifies vehicle parameters and calibrates deflection influence lines, providing a practical means to use on-road vehicles for bridge influence-line calibration without interrupting normal traffic operations. Field validation was carried out on a Yangtze River approach bridge, in which vehicle speeds and wheelbases were determined using acceleration-based axle detection and influence-line features. The proposed method was evaluated using 580 heavy-vehicle passages, with embedded pavement-based WIM (PWIM) and high-precision static weighing data as references. Results show that the LWIM system achieved a mean absolute error of 6.64 %, outperforming the embedded PWIM system (8.56 %) and maintaining over 75 % of vehicle weight estimation errors within 10 %. Performance analysis across weight classes demonstrated mean errors of 14.43 %, 9.81 %, and 6.68 % for vehicles 35 tons, respectively. These findings confirm the proposed LWIM system as a practical, scalable, and cost-effective solution for vehicle load monitoring and health assessment of short- and medium-span bridges.
Shen et al. (Fri,) studied this question.