Automated surface defect detection using line scanner data and 3D model data

Procedia CIRP, vol. 143, pp. 58–61

Abstract

This paper presents an automated three-dimensional surface defect detection methodology for metal components, designed for integration with laser-based remediation systems. The approach aligns depth sensor scans with CAD reference models to identify and categorize surface deviations. Conventional registration methods are sensitive to noise errors and defect-induced deviations, as they typically incorporate all observed points into the alignment process. To ensure reliable alignment under such conditions, the method separates defect exclusion and registration within a two-stage workflow. The primary contribution is a novel anchor point determination algorithm that enables deterministic and unambiguous point cloud registration by deriving four geometrically unique points from Oriented Bounding Boxes at deliberately distinct distances from a reference origin, thereby resolving correspondence ambiguities and enabling stable transformation computation using the Kabsch algorithm. Prior to alignment, defect-free surface regions are estimated using robust preprocessing to prevent defect-induced bias in the reference geometry. Following alignment, signed distance computation categorizes surface points into five deviation classes based on magnitude and direction, providing the localization and classification data required for automated laser parameter selection. By operating on defect-free reference geometries, the method improves alignment stability and enables more reliable defect quantification.

Authors 6

1. Amelie Beye corresponding Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstrasse 17, 52074, Aachen, Germany

2. Jan-Hendrik Koch Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstrasse 17, 52074, Aachen, Germany

3. Florian Hüsing Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstrasse 17, 52074, Aachen, Germany

4. Henning Janssen Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstrasse 17, 52074, Aachen, Germany

5. Christian Brecher Aachen Fraunhofer Institute for Production Technology IPT Laboratory for Machine Tools and Production Engineering WZL

   RWTH Aachen University · Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstrasse 17, 52074, Aachen, Germany

   Laboratory for Machine Tools and Production Engineering WZL of the RWTH Aachen University, Campus-Boulevard 30, 52074 Aachen, Germany

6. Louis Kopf Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstrasse 17, 52074, Aachen, Germany