跨域特征模型之间的关联性

S. Subramani, B. Gurumoorthy
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引用次数: 2

摘要

特征模型之间的关联性是指当一个零件的特征模型发生变化后,该零件的不同特征模型会自动更新。在分布式和并发设计环境中,这是一个重要的需求,在这种环境中,必须通过在不同任务域中所做的更改来维护部件几何形状的完整性。该算法以零件的多个特征模型为输入,通过修改其他特征模型来反映特征模型中某一特征的变化。该算法对未编辑过的模型中的特征卷进行更新,对更新后的特征卷进行分类,得到更新后的特征模型。利用特征面的空间排列和特征之间的邻接关系来隔离视图中受修改影响的特征。基于修改特征的特征体相对于被更新模型的特征体的分类来更新特征体。该算法能够处理所有类型的特征修改,即特征删除、特征创建以及特征位置和参数的更改。与当前自动更新特征模型的技术相比,该算法不使用中间表示,不从低级表示重新解释特征模型,并处理交互特征。给出了典型案例的实施结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Associativity between feature models across domains
Associativity between feature models implies the automatic updating of different feature models of a part after changes are made in one of its feature models. This is an important requirement in a distributed and concurrent design environment, where integrity of part geometry has to be maintained through changes made in different task domains.The proposed algorithm takes multiple feature models of a part as input and modifies other feature models to reflect the changes made to a feature in a feature model. The proposed algorithm updates feature volumes in a model that has not been edited and then classifies the updated volumes to obtain the updated feature model. The spatial arrangement of feature faces and adjacency relationship between features are used to isolate features in a view that are affected by the modification. Feature volumes are updated based on the classification of the feature volume of the modified feature with respect to feature volumes of the model being updated. The algorithm is capable of handling all types of feature modifications namely, feature deletion, feature creation, and changes to feature location and parameters. In contrast to current art in automatic updating of feature models, the proposed algorithm does not use an intermediate representation, does not re-interpret the feature model from a low level representation and handles interacting features. Results of implementation on typical cases are presented.
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