Abstract
The two most important factors in sampling during coordinate verification of a surface are the number of measuring points that accurately represent the surface and the distribution of those points. Three algorithms are developed in this paper for sampling of free-form surfaces at a patch scale (not the entire surface). The three developed algorithms take each patch on the surface as a separate unit and distribute the points within the patch in two steps, namely, sample the most critical points that depend on maximum and minimum Gaussian curvature of each patch and add more points depending on the overall distribution of the most critical points distributed on the surface. In each step of sampling, the maximum difference between the CAD model and the surface created using those sampled points is obtained, and an optimum number of measuring points is determined. This minimizes sampling effort and (non-value-added) measurement time. A comparison is performed between the three proposed algorithms and two well known sampling techniques: the equiparametric approach and the patch-size-based sampling method. The proposed algorithms distribute the points in each patch based on a specific plan. The results show that the developed algorithms help select an efficient number of sampling points.
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Obeidat, S.M., Raman, S. An intelligent sampling method for inspecting free-form surfaces. Int J Adv Manuf Technol 40, 1125–1136 (2009). https://doi.org/10.1007/s00170-008-1427-3
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DOI: https://doi.org/10.1007/s00170-008-1427-3