Research on a high-precision extraction algorithm for aircraft skin seam features

Abstract

The precision measurement of the surfaces of aircraft based on structured light technology is an important development direction of aircraft skin assembly and maintenance. Based on the characteristics of the point cloud in the skin seam area, the height difference mutation method and the slope value maximization method are proposed to extract the edge points of the feature point cloud, achieving the high-precision extraction of the flush and gap of the aircraft skin. First, the 3D point cloud data of the feature region are generated with fringe projection profilometry, and an adaptive matching calibration algorithm is used to calibrate the feature region with high precision. A 3D feature data calculation model is established for both straight line and curve seams, and the edge points of the feature point cloud are extracted with the height difference mutation method and the slope value maximization method to achieve the high-precision extraction of 3D feature data of aircraft skin seams. In this study, an aircraft seam 3D data measurement model is systematically established. This model is suitable for both straight lines and curves. Compared with the algorithm for the feature seam extraction of the slope difference skin, the model has better robustness, and the average measurement error is reduced to approximately one-third of that of the classical algorithm.