A study of a reverse engineering system based on vision sensor for free-form surfaces |
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| Affiliation: | 1. School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200030, People''s Republic of China;2. School of Mechanical Engineering, Tianjin University, Tianjin 300073, People''s Republic of China;1. School of Biology, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, Thailand;2. Department of Animal Science, Faculty of Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel;3. Department of Animal Science, University of Minnesota, St. Paul, MN, USA;1. Laboratory of Chemistry and Endocrinology, University Hospital of Pisa, Via Paradisa 2, 56124 Pisa, Italy;2. Department of Clinical and Experimental Medicine, Section of Endocrinology, University of Pisa, Via Paradisa 2, 56124 Pisa, Italy;1. Molecular Physiology Laboratory, Division of Avian Physiology and Reproduction, ICAR-Central Avian Research Institute, Izatnagar, 243122, India;2. Sálim Ali Centre for Ornithology and Natural History, Anaikatty, Coimbatore 641108, India |
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| Abstract: | Reverse engineering can quickly create a CAD model of a new product, in which, the sensor, sampling planning and surface reconstruction are three crucial elements. In this paper, a reverse engineering system involving a new vision sensor, an improved sampling planning module and a fine surface reconstruction module is developed. A characteristic of the proposed sensor is strong linearity between output and input, obtained by the structure optimization when a simple lens replaces the asperic lens. Back propagation (BP) neural network error compensation heightens accuracy. To increase efficiency of digitization, an improved sampling planning approach is proposed; it is based on surface curvature and tangent line slope of a measured point. In surface reconstruction, a new adaptive extracting approach based on curvature of surface reconstructs the non-uniform rational B-spline (NURBS) surface for the scattered data. The accompanying reverse engineering experiment proves the proposed system to be reliable and efficient. |
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