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Representation And Lightweight Of MBD Product Model WEBGL

Posted on:2021-05-13Degree:MasterType:Thesis
Country:ChinaCandidate:Y W LuFull Text:PDF
GTID:2428330614470103Subject:Computer technology
Abstract/Summary:PDF Full Text Request
With the rapid development of digital design and manufacturing technology,the sharing and exchange of MBD product models become more and more frequent.The mature application of MBD technology in all aspects of the product life cycle has led to the increasing amount of MBD product model data.The traditional model lightweight methods are difficult to meet the lightweight requirements of MBD models multiple level of detail at different stages of the product.Therefore,it is urgent to study the lightweight method of MBD product model.In view of the above situation,the paper takes STEP AP242 as the research object,and focuses on the multi-level detail lightweight method under the premise of MBD product model information representation and retention of semantic information.The specific work includes the following three aspects:1.The product information of MBD model is analyzed from different granularity levels and divided into different levels of detail.Taking the product feature semantic element as the basic unit,the MBD semantic representation method based on the multigranularity semantic model is proposed,which lays a theoretical foundation for the multilayer detail lightweight of MBD product model.2.On the basis of the above,a lightweight method of MBD product model based on improved fireworks algorithm is proposed.Firstly,the importance of product model features is evaluated by using feature evaluation index.Then,the feature evaluation value is used as the parameter to adjust the position and number of fireworks seeds in the fireworks algorithm and the lightweight ratio of different feature areas in the product model.In this way,semantic information and multi-level details can be preserved.3.Combined with WEBGL and Three.js technology,the design and realization of MBD product model lightweight and visualization system are completed.
Keywords/Search Tags:MBD, lightweight, multi-granularity, firework algorithm
PDF Full Text Request
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