Abstract The detection of bridge bottom cracks is required for bridge maintenance. In order to realise the requirement of automatic real-time detection of a bridge structure, an image detection method for cracks in the bottom of the bridge structure using a tethered creeping unmanned aerial vehicle (UAV) is proposed. A high-precision unlimited endurance detection plan based on the tethered creeping UAV is designed to use for the bottom cracks of the bridge structure. The detection scheme applies a high-precision image stitching measurement algorithm for cracks at the bottom of the beam body, which is able to restore a panoramic image. All mainstream filtering methods were evaluated, and it turned out that they are practicable/applicable in various crack images of different shapes. The method is applied to the crack detection in the bottom of bridge structures to ensure the accuracy and efficiency of the system measurement. According to the actual measurement by the laboratory platform, the measurement error using this method is less than 0.1 mm, which meets the requirements of measurement automation. The results of the research represent an initial step towards developing an automatic bridge health monitoring and evaluating system.

中文翻译：

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基于系留爬行无人机的桥底裂缝测量

摘要 桥梁养护需要对桥底裂缝进行检测。为实现桥梁结构自动实时检测的需求，提出了一种基于系留爬行无人机（UAV）的桥梁结构底部裂缝图像检测方法。设计了一种基于系留爬行无人机的高精度无限耐力检测方案，用于桥梁结构底部裂缝检测。该检测方案对梁体底部裂纹采用高精度图像拼接测量算法，能够还原全景图像。对所有主流滤波方法进行了评估，结果证明它们在各种不同形状的裂纹图像中都是切实可行的。将该方法应用于桥梁结构底部裂缝检测，保证了系统测量的准确性和效率。根据实验室平台的实际测量，采用该方法的测量误差小于0.1mm，符合测量自动化的要求。研究结果代表了朝着开发自动桥梁健康监测和评估系统迈出的第一步。