Aircraft Skin Countersink Primitive Extraction From 3-D Measurement Point Clouds via Deep Clustering and Fitting

• Published in: IEEE transactions on instrumentation and measurement 2024, Vol.73, p.1-11
• Main Authors: Chen, Mengqi, Zhou, Laishui, Zhang, Yongming, Chen, Honghua, Wang, Jun
• Format: Article
• Language: English
• Subjects: 3-D measurement point cloud; Aircraft; aircraft skin countersink; Circles (geometry); Clustering; Countersinking; Deep learning; Edge detection; Error detection; Fitting; Image edge detection; Inspection; Least squares method; Measurement methods; Noise measurement; Parameters; Point cloud compression; primitive parameters extraction; similarity clustering (CLU); Skin; Surface fitting; Three dimensional models; weighted least squares; Workpieces
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2024.3427820

To ensure the quality of aircraft assembly, precise 3-D inspection of countersinks in the aircraft skin is crucial. We propose CPE-Net, a multitask countersink primitive extraction network designed for this purpose. CPE-Net employs a 3-D point cloud deep learning network to predict countersink edge points, which are then clustered into paired large and small circles, effectively segmenting each countersink into two circular structures. To overcome the influence of measurement noise and sampling irregularity, we employ a learning-based weighted least squares method to adaptively fit circle parameters. Unlike conventional methods, CPE-Net co-trains the classification (CLA), clustering (CLU), and fitting (FIT) modules using a comprehensive loss function that incorporates edge detection error, CLU error, and circle FIT error. This holistic training approach enhances the quality of the extracted countersinks. The extracted countersink primitive parameters are utilized for geometry calculations, resulting in 3-D quality metric values. Our method undergoes testing on both virtual point cloud data and raw-scan data. Experimental results demonstrate the superior accuracy of our approach compared with the existing extraction methods. Furthermore, through a comparative analysis with detection results from contact measurement methods on practical test workpieces, our countersink extraction method showcases its capability and practicality to achieve precise quality inspection.