Abstract: The methods of Traditional highway bridge inspection face some challenges such as low efficiency,high costs,and delayed response.It is particularly urgent to carry out intelligent inspection for bridge structures that are large in scale but increasingly severe in safety situation.This study takes the Maguohe Extra Large Bridge,a key control project of S101 provincial highway in Yunnan province,as the research object.It automatically acquires high-precision low-altitude remote sensing data by deploying an unmanned automated airport on-site,optimizes the close-range photogrammetry algorithm based on high-precision geographical entities for refined inspection route planning of the bridge,improves the AI algorithm for bridge defect detection based on YOLOv5,conducts slope analysis using the improved M3C2 algorithm,and thereby constructs an intelligent inspection technical route for the bridge.Compared with traditional bridge inspection routes,the proposed method in this study offers more convenient data acquisition,more intelligent route planning,and significantly improved bridge defect detection performance,while enabling effective identification of slope changes.proposed in this paper can provide a new technical approach for the intelligent inspection of bridges in plateau mountainous areas.

Key words: low-altitude unmanned automated airport, defect detection, close-range photogrammetry algorithm, real-scene 3D, AI, slope monitoring