论文标题
为建筑和设施经理开发免费的开源自动建筑物外部裂纹检查软件
Developing a Free and Open-source Automated Building Exterior Crack Inspection Software for Construction and Facility Managers
论文作者
论文摘要
检查裂缝是正确监视和维护建筑物的重要过程。但是，手动裂缝检查是耗时，不一致且危险的（例如在高建筑物中）。由于开源AI技术的开发，可用无人机（UAV）的增加以及智能手机摄像机的可用性，可以自动化建筑物裂纹检查过程。这项研究介绍了使用最先进的细分算法来开发一种易于使用，免费和开源的自动化建筑外部裂纹检查软件（ABECIS），用于建筑和设施经理，以识别具体的裂纹并生成定量和定性报告。使用在现实世界中的无人机和智能手机摄像机和受控实验室环境中收集的图像对Abecis进行了测试。从算法的原始输出中，用于测试实验的工会上的中间交集是（1）0.686，用于使用商用无人机在受控的实验室环境中的室内裂纹检测实验，（2）0.186，用于使用智能手机和（3）0.958使用商业营地的室内裂缝检测的室内裂纹检测，用于施工现场。当人类操作员选择性地消除误报时，这些IOU结果可以显着提高到0.8以上。通常，Abecis最适合室外无人机图像，将算法预测与人类验证/干预相结合提供非常准确的裂纹检测结果。该软件可公开提供，可以下载以进行开箱即用：https：//github.com/smart-nyuad/abecis
Inspection of cracks is an important process for properly monitoring and maintaining a building. However, manual crack inspection is time-consuming, inconsistent, and dangerous (e.g., in tall buildings). Due to the development of open-source AI technologies, the increase in available Unmanned Aerial Vehicles (UAVs) and the availability of smartphone cameras, it has become possible to automate the building crack inspection process. This study presents the development of an easy-to-use, free and open-source Automated Building Exterior Crack Inspection Software (ABECIS) for construction and facility managers, using state-of-the-art segmentation algorithms to identify concrete cracks and generate a quantitative and qualitative report. ABECIS was tested using images collected from a UAV and smartphone cameras in real-world conditions and a controlled laboratory environment. From the raw output of the algorithm, the median Intersection over Unions for the test experiments is (1) 0.686 for indoor crack detection experiment in a controlled lab environment using a commercial drone, (2) 0.186 for indoor crack detection at a construction site using a smartphone and (3) 0.958 for outdoor crack detection on university campus using a commercial drone. These IoU results can be improved significantly to over 0.8 when a human operator selectively removes the false positives. In general, ABECIS performs best for outdoor drone images, and combining the algorithm predictions with human verification/intervention offers very accurate crack detection results. The software is available publicly and can be downloaded for out-of-the-box use at: https://github.com/SMART-NYUAD/ABECIS
