Abstract: Aiming at the problem of efficient retrieval of massive computer aided design(CAD) models in enterprise product manufacturing process,this paper studied a retrieval algorithm based on the content feature of two-dimensionalCAD models,and constructed a retrieval system prototype which can be used for DXF format CAD source file model base.Firstly,through the analysis of the DXF file structure of the two-dimensional CAD model,the rule of the primitive in the model is studied and the shape reconstruction is carried out.Secondly,according to the features of primitive,three kinds of content feature extraction methods are proposed,which are based on statistical histogram,two-dimensional shape distribution and Fourier transform.Finally,a multi-feature fusion framework based on unsupervised learning and similarity calculation method are designed to extract the fusion feature descriptor of the model and realize the retrieval of two-dimensional CAD model.Experiments show that the fusion features extracted in this paper contain more abundant content features and are more effective than single features.The system can be directly used in product customization,product design reuse and other aspects to help enterprises further improve the ability of intelligent manufacturing.

Key words: CAD model retrieval, DXF file, Multi-feature fusion, Unsupervised learning