粗糙集理论在关键功能零件识别中的应用

关键功能零件的识别可以提高装配体模型检索的效率并提高重用水平,同时为自主设计提供关键参考信息.为降低人为因素的影响和评价的主观性,本文提出了一种基于粗糙集理论的关键子装配功能零件的自动识别方法,利用装配体模型自身数据对功能零件的排序过程进行驱动.分析、讨论复杂装配体中零件类型与零件之间的装配连接关系,构建了基于复杂网络...

Application of rough set theory in identification of key functional parts

The identification of key functional parts can improve the retrieval efficiency of assembly model and the reuse level of retrieval, and also provide critical reference information for autonomous design. In order to reduce the subjectivity of the expert system, the rough set theory was introduced into the automatic identification of key subassembly functional parts, and the ranking process of functional parts was driven by the data of the assembly model itself. The characteristics and connection relationships of parts in assembly were analyzed, and assembly model was established based on complex network. The topological layer, part attribute layer data, and part types were extracted as condition attributes and decision attributes. The algorithm based on dynamic hierarchical clustering was used to discretize the decision information table of the subassembly parts. The heuristic reduced algorithm based on attribute importance was adopted to dig knowledge, eliminate redundant condition attributes, and obtain attributes reduction set as well as corresponding attribute weight. Finally, the order of the importance of the subassembly parts with key functions was obtained through comprehensive evaluation. The worm gear reducer model was taken as an example to verify the performance of the proposed method. Experimental results show that the final ranking results of the proposed model were consistent with those of previous research results, and since the model is driven by the assembly model data itself, it is more objective.