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NDT.net Issue - 2019-03 - Articles
NDT.net Issue: 2019-03
Publication: 9th Conference on Industrial Computed Tomography (iCT) 2019, 13-15 Feb, Padova, Italy (iCT 2019)
Session: Poster exhibition
Thu 16:00 Agora
ARTICLE

CAD-based defect inspection with optimal view angle selection based on polychromatic X-ray projection images

Alice Presenti, Jan Sijbers18, Arnold J. Den Dekker, Jan De Beenhouwer15
imec-VisionLab, Department of Physics; University of Antwerpen34, Antwerpen, Belgium

Abstract: X-ray 3D computed tomography (CT) is a non-destructive method that allows inspection of internal components of an object. In the conventional approach, the comparison between the measured projections and the 3D model is performed by processing a CT reconstruction from projection data. The accuracy of the inspection analysis strictly depends on the reconstruction, which can suffer from numerous artifacts. To overcome this problem, we propose a new method that performs inspection directly in the projection space, simulating realistic projections from the computer aided design (CAD) model. Our method bases its strength on the prior knowledge from the CAD data and knowledge about the inspected object itself. When inspecting for defective or missing components, it is not restrictive to assume that the position of a potential deviation from the nominal geometry is approximately known. Therefore, we define regions of interest (ROIs) for feature extraction by simply projecting a component or a volume around it. Furthermore, based on the nominal geometry, we can identify the projection angles for which a certain component is most visible, to restrict the inspection analysis to projections obtained at these angles. Our procedure for quality control is composed of two main steps: the first one must be performed prior to in-line inspection and consists of i) an accurate alignment to calibrate the system geometry and ii) building of libraries of simulated projection data. These libraries are used in the second, in-line step to perform a fast 3D alignment with respect to the position and orientation of the sample. The knowledge of the sample’s orientation allows one to select only a few projection angles for which a potential defect is most visible and perform classification by extracting features and measures from merely the projections at this limited set of angles, for a predefined ROI. In this paper, we motivate and describe our procedure for limited view in-line inspection of defects and validate our method with experiments on real data.

Keywords: Inspection (92), X-ray (39), 3DCT (1), angle selection (1),
*Keywords are freely formed keywords from the authors and thus you may Search also for similar terms.

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