Theory And Method To Model Reconstruction Based On Feature And Constraints

Reverse Engineering (RE) is the important techniques in product innovation and fast manufacturing, also has vast applied foreground in modified design and creative design in automobile, motorcycle, airplane, appliance, molding tool etc. As the key technique within Reverse Engineering—the theories method of the model reconstruction has been the research heat. The paper carries on related work around model reconstruction theories and methods based on features in Reverse Engineering.The thought of model reconstruction based on feature and constraints is to extract parameter from measure data, infer the constraints of these features, and the design idea will be obtained, product can be re-design and the innovation can be carried out. The paper puts forward the model reconstruction frame structure, research in the segmentation of point cloud data, the cross-section profiles information achievement, the recognition and reconstruction of quadratic-surface (QS), puts forward the thought of para-free form surface (PFFS) and some strategies of these surfaces reconstruction. In the process of profiles feature elements and quadratic-surface feature elements recognition, some auto-recognition and inference rules in these feature elements are summarized and researched. Also, these constraints are used in fitting process of these feature elements, and the paper put forward homotopy method to solve theses fitting process.The point data pre-processing is the foundation of model reconstruction; problems related to data cloud processing are focused on. To segment point cloud quickly and exactly, the paper puts forward to compute local curvatures information, then segment these point cloud based on the information. To satisfy the information of PPFS reconstruction, slicing method is used to get profiles information. In the processing of slicing data, a method likes Moving Least-Squares is used to simplified these slicing data. The method don't make coordinate conversion of these point data, the iteration step size is decided by density of slicing point cloud, at last, a point set satisfied profiles accuracy standard has been generated. After point data simplifying, there are some other processing method about point cloud: point set ordering, redundant point eliminating, and feature point extracting, which make solid foundation to profile feature elements recognition.The profiles generation is the key of PFFS reconstruction, at the same time, it play great role in confirm the boundary of reconstructed surface. The paper researched a new idea to reconstruct sketch profiles from slicing point data. At first, make use of sub-step method to get two-dimension profiles by minimal profiles feature element, then according to the feature information of fitting elements, the constraints of these elements have been recognized, and a optimal fitting model to two-dimensions profiles is created, the paper firstly solves the fitting model by homotopy method.Quadric surface fitting method based on feature parameters and constraints and solid features extracting by neural net method are used in accurate reconstruction of CAD model. Before optimal fitting QS, least squares method (LSM) is used to getplane and sphere surface parameters, algebra method is used to get cylinder and cone surface parameters, according to these preliminary parameters, constraints between these quadric surfaces can be recognized, and optimal fitting model based on constraints is constructed. Here presents the homotopy method to solve fitting problems. To some standard feature such as slot, boss, the neural net method is used to recognize as solid feature.Free form surface is most important feature to shape of product such as plane, automobile, motorcycle. The paper put forward a strategy to reconstruct the free form surface—Parameterized Free Form Surface (PFFS), here defines some surface construct by profiles and guiding vector etc as PFFS, and these profiles and guiding vector are parameters of the surface. The paper performs the strategy to reconstruct the PFFS is: firstly, getting parameters of the surface, then selecting suitable constructing method, at last, computing the error between points cloud to surface. The paper researches lofting, sweeping, revolving, net and blending method. To evaluate if the surface is suitable to the point cloud, a quick computing distance from point cloud to surface—tangent plane method has been carried out.Supported by Educational Part Doctor Found (The Theory and Method in Model Reconstruction based features and constraints, project number: 2002033062), the proposed methodology has been approached in Model Reconstruction System Based on Feature and Constraints prototype system.