华南理工大学学报（自然科学版）2025，Vol.53Issue(5)：20-31,12.DOI:10.12141/j.issn.1000-565X.240329
基于图神经网络的B-Rep模型加工特征识别方法
Machining Feature Recognition Method of B-Rep Model Based on Graph Neural Network
摘要
Abstract
Automatic feature recognition is one of the key technologies of intelligent manufacturing.Traditional rule-based recognition algorithms have poor scalability,and the methods based on deep convolutional networks are of low accuracy because they use discrete models as input and the recognition results are difficult to accurately map back to the original CAD model,causing inconvenience in application.In view of these shortcomings,a feature recognition method based on graph neural network,which can directly analyze B-Rep models,is proposed.The method extracts effective characteristic information and geometric information from the B-Rep structures to form a feature descriptor,and then establishes an adjacency graph with high-level semantic information based on the topological structure of the CAD model.By taking the adjacency graph as the input,an efficient graph neural network model is constructed.By introducing a differentiable generalized message aggregation function and a residual connection mechanism,the model possesses stronger information aggregation performance and multi-level feature capture capabilities.What is more,message normalization strategy is used to ensure the stability of the training process and to accelerate the convergence of the model.After the training,the network can directly classify and annotate all faces in the B-Rep model,thereby realizing feature recognition.Experimental results on the public dataset MFCAD++demonstrate that the proposed method achieves an accuracy of 99.53%and an average intersection-over-union ratio of 99.15%,which outperforms other similar studies.Further evaluations using more complex testing cases and typical CAD cases from real engineering applications show that the proposed method is of better generalization ability and adaptability.关键词
加工特征识别/图神经网络/深度学习/计算机辅助设计Key words
machining feature recognition/graph neural network/deep learning/computer-aided design分类
信息技术与安全科学引用本文复制引用
胡广华,代志刚,王清辉..基于图神经网络的B-Rep模型加工特征识别方法[J].华南理工大学学报（自然科学版）,2025,53(5):20-31,12.基金项目
广东省自然科学基金项目(2024A1515011997,2022A1515010806) （2024A1515011997,2022A1515010806）
广州市科技计划项目(2023B01J0046) Supported by the Natural Science Foundation of Guangdong Province(2024A1515011997,2022A1515010806) （2023B01J0046）
