3D Point Cloud Analysis for Detection and Characterization of Defects on Airplane Exterior Surface
3D Point Cloud Analysis for Detection and Characterization of Defects on Airplane Exterior Surface
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DOI：
10.1007/s10921-017-0453-1
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发表时间：
2017-12-01
影响因子：
2.8
通讯作者：
Brethes, Ludovic
中科院分区：
文献类型：
--
作者：
Jovancevic, Igor;Pham, Huy-Hieu;Brethes, Ludovic
三维表面缺陷检测仍然是一项具有挑战性的任务。本文介绍了一种新的自动视觉检测系统，能够检测和表征飞机外表面上的缺陷。通过分析用3D扫描仪收集的3D数据，我们的方法旨在基于局部表面特性识别和提取关于不期望的缺陷（例如凹痕、突起或划痕）的信息。表面凹陷和突起被识别为与理想光滑表面的偏差。对于散乱的点云数据，首先采用移动最小二乘算法对噪声数据进行平滑处理。然后在输入数据中的每个点处估计曲率和法线信息。区域生长分割算法利用点云的局部法向和曲率信息将点云分割为缺陷区域和非缺陷区域。此外，计算每个缺陷区域周围的凸船体，以包容可疑的不规则。最后，我们使用我们的新技术来测量缺陷的尺寸，深度和方向。我们测试和验证了我们的新方法的真实的飞机数据从空中客车A320，不同类型的缺陷。系统的准确性进行评估，通过比较我们的方法与地面实况测量获得的高精度测量设备的测量。结果表明，我们的工作是强大的，有效的和有前途的工业应用。
Three-dimensional surface defect inspection remains a challenging task. This paper describes a novel automatic vision-based inspection system that is capable of detecting and characterizing defects on an airplane exterior surface. By analyzing 3D data collected with a 3D scanner, our method aims to identify and extract the information about the undesired defects such as dents, protrusions or scratches based on local surface properties. Surface dents and protrusions are identified as the deviations from an ideal, smooth surface. Given an unorganized point cloud, we first smooth noisy data by using Moving Least Squares algorithm. The curvature and normal information are then estimated at every point in the input data. As a next step, Region Growing segmentation algorithm divides the point cloud into defective and non-defective regions using the local normal and curvature information. Further, the convex hull around each defective region is calculated in order to englobe the suspicious irregularity. Finally, we use our new technique to measure the dimension, depth, and orientation of the defects. We tested and validated our novel approach on real aircraft data obtained from an Airbus A320, for different types of defect. The accuracy of the system is evaluated by comparing the measurements of our approach with ground truth measurements obtained by a high-accuracy measuring device. The result shows that our work is robust, effective and promising for industrial applications.