Research On Process Feature Recognition Using Delta-volume Decomposition And Combination Strategy

Appropriate feature recognition technology is always considered as an important and effective method for integration of CAD/CAPP/CAM systems. Treating delta-volume of metal machining part as research object, this dissertation researches process feature recognition approach of delta-volume.Delta-volume decomposition and combination strategy is proposed, and some operations such as decomposition,combination and matching are researched, the translation between design and process information is discussed to realize intelligent process feature recognition. The main contributions and works are as follows:(1) The framework of process feature recognition is constructed, then the basis theory, recognition process and the realization method of the proposed process feature recognition approach are analyzed after the current main feature recognition approaches are compared each other.(2) The unified description method of delta-volume procedure models is put forward as Extended Attribute Adjacency Graph (EAAG). All kinds of procedure models related to process feature recognition are defined, whose primary operation modes are expounded. The extraction method of the information of procedure models is discussed, too.(3) The delta-volume decomposition and combination strategy is researched, which includes the generation theory and description method of partition surfaces, the creating and ordering and conflicts resolving of the rules for decomposing and combining the delta-volumes. In addition, some phenomenons are analyzed such as new-adding and losing effectiveness of partition surfaces and multi-combination of delta-volumes.(4) The information transferring and processing during the process of feature recognition are researched. Locating capability of selected surfaces is computed, and then location program is generated automatically. Small Displacement Torsor (SDT) theory is used to describe process tolerances of operation cut volumes, and operation tolerance net is organized, then the process tolerance stack-up models are constructed. Using dynamical niche sets-based cooperative evolutionary algorithm, operation tolerances assignment is achieved.(5) The function on process feature recognition is researched and realized. Its development goals, environments and tools are mentioned. More than ten sub-functions are developed, including generation, decomposition and combination of delta-volumes. At last, one application case is afforded to show the primary flow of the given functions.The proposed approach on process feature recognition based on delta-volume decomposition and combination strategy is not only helpful to enhance the intelligence of process feature recognition, but also provides an effective way to integrate CAD/CAPP, with certain theory significance and practice application values.