A grid-structured intelligent coating sensor system for directional crack monitoring in steel bridges

Coating-based sensors have demonstrated great potential for fatigue crack monitoring in the aerospace industry. However, their application in steel bridges remains limited due to constraints in fabrication methods, sensing principles, and cost-effectiveness. This study proposes a low-cost, scalable crack monitoring system tailored for steel bridge structures, achieving real-time crack tracking and geometric reconstruction through material optimization, innovative sensor design, and streamlined system integration. A self-developed conductive ink balances formulation simplicity with high performance, offering reliable conductivity and environmental stability under harsh conditions. The sensor is fabricated via screen-printing, enabling rapid and cost-effective production. Powered by an STC89C52 microcontroller and supported by Python-based processing and Matplotlib rendering, the system allows real-time visualization of crack paths. Experimental results under various crack patterns and temperatures confirm the system’s robustness, achieving a monitoring resolution of 0.8 mm, direction and length identification errors below 1 mm, and stable performance across a 0°C–100°C temperature range. These findings demonstrate the system’s strong potential for practical deployment in steel bridge crack monitoring.