An ellipsoidal mirror is a soft X-ray reflective focusing device. We are developing precise ellipsoidal mirrors based on an electroforming process. To improve the fabrication process, three-dimensional shape measurements with a high accuracy are required. In this research we develop a method to measure ellipsoidal shapes by industrial X-ray computed tomography (CT). The X-ray CT process consists of measuring the mirror shape and determining the parameters of the ellipsoid. We also evaluate the reproducibility of X-ray CT measurements and clarify that the accuracy is at the 5-m level.
As a method of non-destructive internal inspection, X-ray computed tomography (CT) is used not only in medical applications but also for product inspection. Some assembled products can be divided into separate components based on density, which is known to be approximately proportional to CT values. However, components whose densities are similar cannot be distinguished using the CT value driven approach. In this study, we proposed a new component extraction algorithm from the CT volume, using a set of voxels with an assigned CT value with the surface mesh as the template rather than the density. The method has two main stages: rough matching and fine matching. At the rough matching stage, the position of candidate targets is identified roughly from the CT volume, using the template of the target component. At the fine matching stage, these candidates are precisely matched with the templates, allowing the correct position of the components to be detected from the CT volume. The results of two computational experiments showed that the proposed algorithm is able to extract components with similar density within the assembled products on CT volumes.
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