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Masonry Crack Detection Application of an Unmanned Aerial Vehicle

机译:无人驾驶飞行器的砌体裂缝检测应用

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摘要

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:基础设施评估的主要方法是目视检查。大量和规模的检查通常使其难以编目所识别的损坏的位置,尺寸和严重程度。几种无损方法可用于检测声发射和超声,但是它们需要安装许多传感器,通常涉及预定区域中的测量,并且通常需要后处理。尽管基于图像的裂纹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的优点。此外,使用图像拼接可以提供对整个结构的健康的综合评估。该方法也可以使用无人驾驶飞行器(UAV)施加。本文讨论了在无人机上自动裂缝检测和实施中的重大挑战。

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