Research On Key Technology In Model Reconstruction From Optical Scanning And CMM Data

Optical scanning system and three coordinate measuring machines (CMMs) are digitization equipments widely used in reverse engineering. The combined use of both satisfies the application requirements of reverse engineering for high accurate and high efficient digitization. The appearance of multi-sensor combined measuring system also provides the hardware foundation and support for the combination. The exising model construction methods in reverse engineering are mainly based on the similar data which has the same density and accuracy. In order to satisfy the new requirement of the modern digtitization system for model construction method and make up the deficiency of model construction method and software, the method and key technologies of model reconstruction from optical scanning and CMM data are researched in this thesis.Firstly, the strengths and weaknesses of optical scanning system and CMM and their effect for model reconstruction were analyzed by experimentions. Study cases proved these two ditigition methods were complementary. Therefore, method of model reconstruction from optical scanning and CMM data were provided. This thesis also gave a detailed description about the framework, research contents and key technologies which offer the direction for the further study.The optical scanning data were expressed by triangular mesh model. Estimation on differential geometric properties of triangular mesh model was studied. The provided method of curvature estimation can identify the potential anomalous regions of Voronoi method through choose the 2-ring neighbor of each vertex in these regions as k-ring neightbor, using local paraboloid fitting corrected the curvature. Although the accuracy of the provided method was between the Voronoi and local paraboloid fitting, its operation efficiency was higher than local paraboloid fitting. This method was not easy to be effected by triangle shape and had some ability to suppress noises due to introducing of the local paraboloid fitting. Curvature visualization was also realized based color index and histogram equalization algorithm in order to clearly identify the concave or covex features and anomalous regions of curvature estimation.A step and robust segmentation method was provided using normal as a metric. Firstly, mesh normals were filtering through the extension of mean shift. Then a K-means algorithm according to the normal vectors was used by means of chosen fourteen directions as clustering centers. After that initial segmentation was completed using region grow algorithm. Patches merging was the last step, using curvedness as a metric to recognize regular surfaces which are potential regions corresponding with CMM measuring features.Registration between CMM and optical scanning data was researched. In the case of without optical scanning blind areas, a registration method was proposed, in which primitive artifacts were not required as datum, three pairs of points were selected to compute a transform matrix for initial registration. Afterwards, in order to get corresponding points, point set from CMM measurement was projected to nearest triangular mesh constructed from optical scanning data, and the transformation could be achieved by iterative method. This method realized the registration of point sets of non-corresponding points. When having optical scanning blind areas, a registration method using work table was presented, and improved three points location algorithm was used through the middle point of the line segment connected two datum marks instead of initial datum marks. Registration errors of several registration methods were compared for further confirm the feasibility of this improved method.Data merging at regular surfaces based mesh segmentation and registration was realized in order to delete the triangles overlapping with CMM measuring data. According to the data merging at free-form surfaces, this thesis presents an adaptive data merging method which was completed by adaptive mesh segmentation based CMM measuring features and identification of merging regions based on the angle condition. The method would enable to create the customized model and deformation because it might shorten the additional scanning time. It will be practically useful for the surface modification based on the physical part changes, free-form surface design and rapid prototyping manufacturing. The reconstruction methods of regular suface and free-form surface have been given, and then realize the model reconstruction from optical scanning and CMM data instructed by strategy for optimization model reconstruction.