Surface Parameter Measurement of Braided Composite Preform Based on Faster R-CNN

摘要

Pitch length and surface braiding angle are two important parameters of braided composite preforms. In this paper, a method based on Faster R-CNN is proposed to measure the two parameters. First, after image acquisition, a fabric image database including initial cropped images, augmented images, and target images is established. Then, the target images are classified into four categories according to the gray change characteristics. Third, a Faster R-CNN fabric detection model is trained on the fabric image database. Fourth, targets are detected by the trained network, and corners are detected based on the detected targets. Finally, pitch lengths and surface braiding angles are measured based on the detected corners. Experimental results show that the proposed method achieves the automatic measurement of pitch lengths and surface braiding angles of 2D and 3D braided composite preforms with high accuracy.