No description available.

Zugl.: Köln, Univ., Diss., 2008/2009

Graduate

No description available.

Thesis (PhD)--University of South Australia, 2001

Stuttgart, Univ., Diplomarb., 2002.

Zugl.: Saarbrücken, Univ., Diss., 2009

Zugl.: Hannover, Universiẗat, Diss., 2009.

Reverse engineering of geometric models is the process of creating a computer aided model from an existing physical part so that subsequent manufacturing processes may be implemented. Applications of reverse engineering can range from the production of molds and dies from wood or clay models to the creation of replacement parts from worn existing machinery. In reverse engineering, both contact and non-contact measurement probes are used to gather measured surface points. However, due to the nature of these instruments, both the direction of the probe during measurement and the conversion of the gathered data to the appropriate computer aided models are currently very difficult. This thesis addresses some of these problems. A stereo vision system employing neural network based image segmentation is implemented to automatically generate probe paths for either a touch trigger probe or an optical laser scanner. A fuzzy logic based iterative geometry fitting algorithm is used to fit geometric primitives to measured surface data. As modern computer aided drafting programs utilise parametric modelling methods and topology information, regarding the association of neighbouring surface patches is determined from the fitted geometric entities. Finally, utilising the extracted geometric and topology information, specific surface features, such as comers, slots and steps are detected using a feed-forward neural network. The computational tools in this thesis provide methods that reduce the time and effort required to geometrically reverse engineer an existing physical object. / Graduate

Indiana University-Purdue University Indianapolis (IUPUI) / Close range, image based photogrammetry and LIDAR laser scanning technique are commonly utilized methodologies to snap real objects.3D models of already existing model or parts can be reconstructed by laser scanning and photogrammetry. These 3D models can be useful in applications like quality inspection, reverse engineering. With these techniques, they have their merits and limitations. Though laser scanners have higher accuracy, they require higher initial investment. Close-range photogrammetry is known for its simplicity, versatility and e ective detection of complex surfaces and 3D measurement of parts. But photogrammetry techniques can be initiated with comparatively much lower initial cost with acceptable accuracy. Currently, many industries are using photogrammetry for reverse engineering, quality inspection purposes. But, for photogrammetric object reconstruction, they are using di erent softwares. Industrial researchers are using commercial/open source codes for reconstruction and another stand-alone software for reverse engineering and mesh deviation analysis. So the problem statement here for this thesis is to integrate Photogrammetry, reverse engineering and deviation analysis to make one state-of-the-art work ow. xx The objectives of this thesis are as follows: 1. Comparative study between available source codes and identify suitable and stable code for integration; understand the photogrammetry methodology of that particular code. 2. To create a taskpane add-in using API for Integration of selected photogrammetry methodology and facilitate methodology with parameters. 3. To demonstrate the photogrammetric work ow followed by a reverse engineering case studies to showcase the potential of integration. 4. Parametric study for number of images vs accuracy 5. Comparison of Scan results, photogrammetry results with actual CAD data