【摘要】 为了有效提高近净模型的制造质量和效率，提出一种基于图分解的三维打印近净模型生成方法。首先通过添加多个属性构造扩展属性邻接图。其次基于特征基面和特征基环对扩展属性邻接图进行分解，并对分解子图进一步优化后得到条件子图。再次结合定义的特征规则库开展特征识别并将子图分类，采用机械加工余量驱动建模生成初步近净模型，通过手动优化得到符合工艺要求的近净模型。最后通过多个应用实例和体积对比验证了该方法的有效性。更多还原

【Abstract】 In order to effectively improve the manufacturing quality it transforms directly printing part design model into printing the near-net model. A graph decomposition-based 3D printing near-net model generation method is proposed. Firstly, an extended attribute adjacency graph(EAAG) is constructed by adding multiple attributes,and secondly, the extended attribute adjacency graph is decomposed based on the feature base face and feature base wire, and the conditional subgraph is obtained after further optimization of the decomposed subgraph, and then the feature recognition is carried out in combination with the defined feature rule library, and the subgraph is classified. The machining allowance-driven modeling generates a preliminary near-net model, and a near-net model that meets the process requirements is obtained by manual optimization. Finally, the effectiveness of the method is verified by multiple application instances and volume comparisons.更多还原