Journal of Engineering Research

Aiming at the problem of cycle over-limit of large cross-river continuous beam Bridges due to the limitation of road closure Windows and detection resources, this paper takes a special bridge with a main span of 120 m as a case, constructs a "resource - risk - economy" ternary diagnostic model, and identifies the core factors affecting cycle compression. On this basis, a multi-channel collaborative scheduling strategy integrating unmanned aerial vehicles, cable robots and vehicle-mounted equipment is proposed, and a BIM-driven dynamic disease prediction system is introduced to achieve differentiated detection cycles matched according to risk levels. After the optimization was implemented, the road closure time was reduced by 62%, the cycle for key areas was shortened to 12 months, the reliability index β was improved by 0.8, and the annual cost was saved by 6.72 million yuan. The research has established a closed-loop mechanism of "collection - prediction - scheduling - feedback", providing a standardized technical path for the intelligent operation and maintenance of long-span Bridges.

Bridge inspection; Cycle optimization; Reliability analysis; Resource scheduling; BIM decision-making