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Conference Papers Year : 2024

Defect Characterization on Complex Shape Aeronautical Parts via 3D Point Cloud Processing

Igor Jovančević
Jean-José Orteu

Abstract

This paper presents an approach to characterizing defects - a process that consists of accurate measurement of their geometric properties such as depth and surface area, assuming that the defect detection process has been successfully performed previously. Our methodology for addressing this problem involves three key steps. The first is to reconstruct an ideal or defectfree surface using scattered points obtained from a point cloud scan of the inspected part. Subsequently, the distance from each cloud point to this surface is computed, and points at a distance higher than a specified threshold are identified as defect points. The maximum of these distances corresponds to the depth of the defect. Finally, the minimal 3D bounding box encapsulating the defect points is determined, where the two largest dimensions of this box represent the length and width of the identified defect.
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Dates and versions

hal-04623874 , version 1 (25-06-2024)

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Marija Džaković, Igor Jovančević, Velibor Došljak, Jean-José Orteu. Defect Characterization on Complex Shape Aeronautical Parts via 3D Point Cloud Processing. MECO 2024 - 13th Mediterranean Conference on Embedded Computing, Jun 2024, Budva, Montenegro. pp.218-222, ⟨10.1109/MECO62516.2024.10577809⟩. ⟨hal-04623874⟩
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