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Three-dimensional point cloud analysis for automatic inspection of complex aeronautical mechanical assemblies

Abstract : We present a robust approach for detecting defects on an aircraft electrical wiring interconnection system in order to comply with the safety regulations such as the forbidden interference and allowed bend radius of cables and/or harness in mechanical assemblies. For this purpose, we exploit 3-D point clouds acquired with a 3-D scanner and the 3-D computer-aided design (CAD) model of the assembly being inspected. Our method mainly consists of two processes: an offline automatic selection of informative viewpoints and an online automatic treatment of the acquired 3-D point cloud from said viewpoints. The viewpoint selection is based on the 3-D CAD model of the assembly and the calculation of a scoring function, which evaluates a set of candidate viewpoints. After the offline viewpoint selection is completed, the robotic inspection system is ready for operation. During the online inspection phase, a 3-D point cloud is analyzed for measuring the bend radius of each cable and its minimum distance to the other elements in the assembly. For this, we developed a 3-D segmentation algorithm to find the cables in the point cloud, by modeling a cable as a collection of cylinders. Using the segmented cable, we carried out a quantitative analysis of the interference and bend radius of each cable. The performance of the inspection system is validated on synthetic and real data, the latter being acquired by our precalibrated robotic system. Our dataset is acquired by scanning different zones of an aircraft engine. The experimental results show that our proposed approach is accurate and promising for industrial applications.
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Submitted on : Wednesday, April 29, 2020 - 10:22:31 AM
Last modification on : Wednesday, August 5, 2020 - 3:46:19 AM

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Hamdi Ben Abdallah, Jean-José Orteu, Igor Jovančević, Benoît Dolives. Three-dimensional point cloud analysis for automatic inspection of complex aeronautical mechanical assemblies. Journal of Electronic Imaging, SPIE and IS&T, 2020, 29 (04), pp.041012-1-041012-22. ⟨10.1117/1.JEI.29.4.041012⟩. ⟨hal-02557867⟩

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