Research On Technique Of Product Information Acquisition Based On Multi-Granularity

The description, transfer and acquisition of product information is a basic problem in the area of computer-aided design and computer graphics. Engineering drawing interpretation (EDI) is a kind of acquisition behavior of product information on the base of engineering drawing. It emerged as a vibrant area of interdisciplinary research, attracting the efforts of computer graphics scientists, artificial intelligent scientists, cognitive psychologists and etc. This research can be traced back to sixties in twenty century, whereas the result is still far from the desired purpose up to date.After analyzing the current algorithms, the problems existed in them and the root reasons lying behind are discussed. Then the primitive recognition and interpretation are taken as the research emphasizes of this dissertation. The main process includes performing high-level analysis of the drawing information on vector data in 2D orthographic form, mining engineering semantics from the drawing information, and obtaining the corresponding information of primitive by using engineering semantics. The result could be used as a basis for 3D reconstruction, and to provide product information for CAD (computer-aided design), CAPP (computer-aided process planning) and CAM (computer-aided manufacturing). The main work of the dissertation is as follows:The knowledge-based granularity analysis method of engineering drawing information is put forward by introducing the concept of granularity into the process of EDI. This method is composed of three main steps, namely cognition-based decomposing of drawing interpretation goal, object-oriented partitioning of knowledge and knowledge-directed classification of drawing information. The drawing information classification is expanded into the total procedure of EDI, which could be treated as the information resource for product information acquisition with reasonable organization structure.The classification-based acquisition technique of engineering semantics is presented. On the base of engineering semantics classification, the contribution of different kind of semantics and the relationships among them in EDI are analyzed. The class acquisition of expression mode semantics, projection relationship semantics and dimension constraint semantics, and integration acquisition technology of tangency combined relationship, interpenetrate combined relationship and intersectedcombined relationship are emphatically introduced, which lay the foundation for further primitive recognition. By using this method, information processing could be simplified, and interpretation reliability could also be enhanced.The shape similarity-based recognition method of non-intersected primitive is proposed. By analyzing the features, the implication and the property of graphic similarity, the computation method of similarity degree is provided. Then the features of graphic are described by means of graph, while the method of graphic coding mode is presented. In the end, a hierarchical discrimination algorithm of graphic similarity is put forward based on above methods. Compared with the old ones, some improvements are obtained by using this method, such as pattern recognition scope, speed of pattern searching and matching, etc. Furthermore, the new algorithm has stronger flexibility and stability.The information acquisition technique of intersected primitive based on combined relationship is provided. With the help of obtained engineering semantics, the correlative projections implying combined relationship among primitives are defined as combined factor. Then combined relationship table is established. Finally, the combined relationship table is used to recognize primitives with different kinds of combined relationships. Because the technique establishes the connection between the 2D combined factors and their homologues 3D combined relationships, the search space could be limited and the recognition shape could be extended.The strategy for product information acquisition is designed, including the...