智能拉深件工艺设计系统的关键技术

应用特征技术和人工智能技术，建立了基于特征的智能拉深类零件工艺设计系统框架，研究并实现了其中的关键技术。由于拉深成形中工艺中零件形成的特征方法，面向拉深的特征以复杂的曲面特征为主，讨论了拉深类零件中几何特征向工艺特征的转换，提出了模糊决策表技术在工艺设计中的应用，应用ＢＰ神经网络方法预测了方盒件理想毛坯外形，通过人工智能技术建立起基于特征的工艺设计知识库，使特征技术能应用于拉深类零件的工艺设计中。

Key Technologies in Intelligent CAPP System for Deep-Drawn Parts

The technologies including feature classification of deep drawn parts,feature recognition,feature based knowledge base,decision tables and neural networks,were integrated together in feature based intelligent CAPP system for deep drawn parts in this paper. A framework of feature based intelligent CAPP system was established using feature technology and AI technology. The key technologies were implemented.Due to the particularity of deep drawing process,the deep drawn component oriented geometry feature is a complex surface feature.Transformation from surface feature to process feature of deep drawn parts was discussed.Application of fuzzy decision tables in process planing was presented.An ideal blank shape of square box was predicted using BP neural network. The feature based knowledge base for process planning was established using AI technology,and the feature technology can been applied to CAPP system for deep drawn parts.