A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segme...A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.展开更多
Non-uniform rational B-spline (NURBS) curves and surfaces are very important tools for model- ling curves and surfaces. Several important details, such as the choice of the sample points, of the parame- terization, an...Non-uniform rational B-spline (NURBS) curves and surfaces are very important tools for model- ling curves and surfaces. Several important details, such as the choice of the sample points, of the parame- terization, and of the termination condition, are however not well described. These details have a great in- fluence on the performance of the approximation algorithm, both in terms of quality as well as time and space usage. This paper described how to sample points, examining two standard parameterizations: equi- distant and chordal. A new and local parameterization, namely an adaptive equidistant model, was pro- posed, which enhances the equidistant model. Localization can also be used to enhance the chordal parameterization. For NURBS surfaces, one must choose which direction will be approximated first and must pay special attention to surfaces of degree 1 which have to be handled as a special case.展开更多
基金This project is supported by General Electric Company and National Advanced Technology Project of China(No.863-511-942-018).
文摘A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.
基金Supported by the Company ProCAEss GmbH, Landau in der Pfalz, Germany
文摘Non-uniform rational B-spline (NURBS) curves and surfaces are very important tools for model- ling curves and surfaces. Several important details, such as the choice of the sample points, of the parame- terization, and of the termination condition, are however not well described. These details have a great in- fluence on the performance of the approximation algorithm, both in terms of quality as well as time and space usage. This paper described how to sample points, examining two standard parameterizations: equi- distant and chordal. A new and local parameterization, namely an adaptive equidistant model, was pro- posed, which enhances the equidistant model. Localization can also be used to enhance the chordal parameterization. For NURBS surfaces, one must choose which direction will be approximated first and must pay special attention to surfaces of degree 1 which have to be handled as a special case.
