Bridge defects are important indicator for the bridge safety assessment. Considering the cost and inefficiency of the traditional method, the UAV system applied for bridge crack inspection is a better choice. Therefore, we have configured a bridge inspection UAV system with SLR camera, laser rangefinder. First, we have carried an evaluation experiment to determine the distance range of stable imaging for planning the safer bridge inspection route based on the special UAV system. Then, the crack recognition method combining neural network and support vector machine is used to locate and extract the bridge cracks, and then, the actual cracks are calculated according to the optical principle. Finally, a case study of the Xiangjiang-River bridge inspection is carried out to verify the feasibility of bridge defects recognition based on this UAV system, achieving above 90% in the crack width recognition, which provides a better platform for bridge inspection.
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering