Abstract
Bridges are an indispensable element of modern infrastructure, while the difference in maintenance between the small and medium-sized bridges and large bridges is huge. At present, the health assessments of the small and medium-sized bridges still depend on manual detection, which requires a lot of manpower and material resources with limited efficiency. To overcome these issues, this study proposes a novelty vision-based displacement measurement solution utilizing a smartphone, which includes multiple image recognition methods for different application scenarios and further constructs a complete management and maintenance system. The proposed system is validated in the laboratory tests with a cable-stay bridge and field tests on a continuous plate bridge. Moreover, the field experiments on a continuous girder bridge with far measuring distance under diverse lighting conditions were conducted, investigating the measurement effects of various image methods and providing beneficial explorations for the development of detection and monitoring technology on the small and medium-sized bridges.
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