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Masonry Crack Detection Application of an Unmanned Aerial Vehicle

机译:无人机砌体裂缝检测应用

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The predominant method for infrastructure evaluation is visual inspection. The large number and scale of inspections often make it difficult to catalog the location, size, and severity of the identified damage. Several nondestructive methods can be used to detect cracks, such as acoustic emission and ultrasound, but they require the installation of many sensors, typically involve measurements in a predetermined area, and often require post-processing. Though image-based crack detection is limited to inspecting surface cracks, it has advantages including speed, repeatability, and large area coverage. Furthermore, the use of image stitching can provide a comprehensive assessment of the health of the entire structure. This method could also be applied using an unmanned aerial vehicle (UAV). This paper discusses major challenges in automated crack detection and implementation on UAVs.
机译:基础结构评估的主要方法是外观检查。大量的检查工作经常使分类发现损坏的位置,大小和严重程度变得困难。可以使用几种非破坏性方法来检测裂缝,例如声发射和超声,但是它们需要安装许多传感器,通常涉及在预定区域中进行测量,并且通常需要后处理。尽管基于图像的裂缝检测仅限于检查表面裂缝,但它具有包括速度,可重复性和大面积覆盖范围在内的优点。此外,图像拼接的使用可以对整个结构的健康状况提供全面的评估。该方法也可以使用无人飞行器(UAV)来应用。本文讨论了无人机自动裂缝检测和实施中的主要挑战。

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