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Image-based crack assessment of bridge piers using unmanned aerial vehicles and three-dimensional scene reconstruction

机译:使用无人机航空公司和三维场景重建的桥墩基于图像的裂缝评估

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Abstract Crack assessment of bridge piers using unmanned aerial vehicles (UAVs) eliminates unsafe factors of manual inspection and provides a potential way for the maintenance of transportation infrastructures. However, the implementation of UAV‐based crack assessment for real bridge piers is hindered by several key issues, including the following: (a) both perspective distortion and the geometry distortion by nonflat structural surfaces usually appear on crack images taken by the UAV system from the pier surface; however, these two kinds of distortions are difficult to correct at the same time; and (b) the crack image taken by a close‐range inspection flight UAV system is partially imaged, containing only a small part of the entire surface of the pier, and thereby hinders crack localization. In this paper, a new image‐based crack assessment methodology for bridge piers using UAV and three‐dimensional (3D) scene reconstruction is proposed. First, the data acquisition of UAV‐based crack assessment is discussed, and the UAV flight path and photography strategy for bridge pier assessment are proposed. Second, image‐based crack detection and 3D reconstruction are conducted to obtain crack width feature pair sequences and 3D surface models, respectively. Third, a new method of projecting cracks onto a meshed 3D surface triangular model is proposed, which can correct both the perspective distortion and geometry distortion by nonflat structural surfaces, and realize the crack localization. Field test investigations of crack assessment of a real bridge pier using a UAV are carried out for illustration, validation, and error analysis of the proposed methodology.
机译:摘要使用无人机(无人机)桥墩裂纹评估(无人机)消除了手动检查的不安全因素,为维护运输基础设施提供了潜在的方法。然而,通过几个关键问题阻碍了对真实桥接码头的无人基于UAV的裂缝评估,包括以下几个关键问题:(a)非污水结构的透视失真和非流动结构表面的几何失真通常出现在UAV系统拍摄的裂缝图像上码头表面;然而,这两种扭曲难以同时纠正; (b)由近距离检查飞行UAV系统拍摄的裂缝图像部分成像,仅包含码头的整个表面的一小部分,从而阻碍了裂纹定位。在本文中,提出了一种使用UAV和三维(3D)场景重建的桥接码头的新的基于图像的裂缝评估方法。首先,讨论了基于UAV的裂缝评估的数据采集,提出了UAV飞行路径和桥接码头评估的摄影策略。第二,进行基于图像的裂缝检测和3D重建,以分别获得裂缝宽度特征对序列和3D表面模型。第三,提出了一种将突出裂缝突出到网状3D表面三角模型的新方法,这可以通过非污水结构表面校正透视失真和几何失真,并实现裂纹定位。使用UAV进行实际桥墩裂纹评估的现场测试调查,用于说明,验证和误差分析所提出的方法。

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