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首页> 外文期刊>Computer-Aided Civil and Infrastructure Engineering >Automated crack evaluation of a high-rise bridge pier using a ring-type climbing robot
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Automated crack evaluation of a high-rise bridge pier using a ring-type climbing robot

机译：使用环形攀岩机器人自动化高层桥墩的裂缝评估

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摘要

This article proposes a deep learning-based automated crack evaluation technique for a high-rise bridge pier using a ring-type climbing robot. First, a ring-type climbing robot system composed of multiple vision cameras, climbing robot, and control computer is developed. By spatially moving the climbing robot system along a target bridge pier with close-up scanning condition, high-quality raw vision images are continuously obtained. The raw vision images are then processed through feature control-based image stitching, deep learning-based semantic segmentation, and Euclidean distance transform-based crack quantification algorithms. Finally, a digital crack map on the region of interest (ROI) of the target bridge pier can be automatically established. The proposed technique is experimentally validated using in situ test data obtained from Jang-Duck bridge in South Korea. The test results reveal that the proposed technique successfully evaluates cracks on the entire ROI of the bridge pier with precision of 90.92% and recall of 97.47%.
机译：本文提出了一种使用环形攀岩机器人的高层桥墩基于深度学习的自动裂缝评估技术。首先，开发出由多视觉摄像头，攀爬机器人和控制计算机组成的环型攀岩机器人系统。通过在具有特写扫描条件的目标桥墩沿着目标桥接码头在空间移动攀爬机器人系统，连续获得高质量的原始视觉图像。然后通过特征控制的图像拼接，基于深度学习的语义分割和基于欧几里德距离变换的裂缝量化算法来处理原始视觉图像。最后，可以自动建立目标桥接码头的感兴趣区域（ROI）的数字裂缝图。通过从韩国的Jang-Duck Bridge获得的原位测试数据实验验证所提出的技术。测试结果表明，该技术成功地评估了桥墩整个投资回报率的裂缝，精度为90.92％，召回为97.47％。

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