Dynamic Recognition Research of Parts Information of MC - VE Based on the Optimal Binary Tree and Fuzzy Reasoning

Abstract

Part information is the research object with the background of cloud manufacturing. And parts information are acquired and recognized. The characteristic and demand of part information are analysed of a mixed cloud virtual enterprises (MC-VE) based on the Internet and Internet of thing. Part information content and information process are summarized of the MC -VE. The sources and the characteristics of the part information are analysed. The retrieval method of parts information is two-dimension code, which can be concluded basic needed information and the context of the information associated with it of MC-VE. Identifying and obtaining of parts geometry information is combined by using the theory of the optimal binary tree method. The information matching of surface, side, between side and surface adopts the method of fuzzy reasoning in the geometry information of parts. The research works on matching and combination are respectively done between the typical side, typical side and typical surface. It is concluded that common matching rules and combination conclusion of the combination of geometry information. And it implements dynamic combination and recognition of the parts geometry information under the environment of MC-VE. It provides reference for acquiring the parts geometry information of MC-VE in heterogeneous and long-distance.