The application discloses a CAD model through-hole
feature recognition and
processing method based on a graph neural network, comprising the following steps: constructing a surface adjacency graph according to the B-Rep representation of a CAD model; extracting differential geometric information and attribute information of each surface to construct a node initial
feature vector; classifying each surface by using a graph neural network to determine a through-hole surface recognition result; performing triangular
subdivision on the CAD model, deleting all grids located on the through-hole surface, applying a hole filling
algorithm to repair the grid gap, determining a final grid model with the through-hole feature removed, or associating the surface
label with a grid generation
algorithm to guide grid generation and determine the finally generated anisotropic grid. The application comprehensively improves the recognition accuracy,
processing efficiency and output quality while maintaining the lightweight of the model, and provides reliable
technical support for the CAD / CAE integrated process.