Abstract

The digital manufacturing deviation inspection can be used to assess the dimension, form, and position errors, which is more efficient, more consistent, and more robust than manual inspection. CAD models are used as the nominal data and compared with the scanned data of parts to obtain manufacturing errors. CAD model tessellation is a pivotal step in deviation inspection, which directly determines the reliability of analytical results. It requires that the generated triangle mesh has dense vertices, high approximation accuracy, and consistent orientation. A single surface patch tessellation method is proposed, and the adaptive quadtree is first constructed to divide the domain into small spatial grids in the parameter space of the patch; then, a clip-based method is presented to triangulate boundary grids, and inner grids could be triangulated by the constrained Delaunay triangulation method. Furthermore, the mesh patches should be spliced and reoriented consistently, which is very important for deviation analysis. To solve this problem, a robust gap healing method based on merging boundary points of patches is developed, so that all boundary vertices of adjacent patches could completely coincide along the common edges, and all mesh patches would be stitched into a complete mesh without gaps. Finally, the face normal of mesh is adjusted to obtain a consistent orientation. Experiments on industrial CAD models demonstrate that the proposed method could realize faster and more robust mesh generation than the state-of-the-art approaches, including three commercial and two open-source software.

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