Manufacturing Feature Recognition Method Based on Graph and Minimum Non-Intersection Feature Volume Suppression

Automatic manufacturing feature recognition (AFR) is a critical technology for realizing CAD/CAPP/CAM integration in the era of intelligent manufacturing. Despite the numerous feature recognition approaches that have been proposed, the recognition of intersecting features remains a challenge. The most important reason is that the boundaries of features and their geometric topological information are altered or destroyed when interacting with other features. To address this problem, this paper proposes a manufacturing feature recognition method based on graph and minimum non-intersection feature volume suppression. Firstly, the geometric and topological information of a part is extracted and represented as an attributed adjacency graph. Then, a subgraph isomorphism algorithm is designed to recognize the features corresponding to each subgraph. After that, a method to construct and suppress the minimum non-intersection volume of the recognized features is introduced to repair the boundaries of intersecting features. On this basis, intersecting features are separated and recognized at different stages. The experimental results indicate that the proposed approach is effective in recognizing intersection features. Moreover, the recognition result of the proposed method incorporates the surface and volume of a feature, providing enriched feature information for engineering applications.