Abstract
High-accuracy surface measurement of large aviation parts is a significant guarantee of aircraft assembly with high quality. The result of boundary measurement is a significant parameter for aviation-part measurement. This paper proposes a measurement method for accurately measuring the surface and boundary of aviation part with feature compression extraction and directed edge-point criterion. To improve the measurement accuracy of both the surface and boundary of large parts, extraction method of global boundary and feature analysis of local stripe are combined. The center feature of laser stripe is obtained with high accuracy and less calculation using a sub-pixel centroid extraction method based on compress processing. This method consists of a compressing process of images and judgment criterion of laser stripe centers. An edge-point extraction method based on directed arc-length criterion is proposed to obtain accurate boundary. Finally, a high-precision reconstruction of aerospace part is achieved. Experiments are performed both in a laboratory and an industrial field. The physical measurements validate that the mean distance deviation of the proposed method is 0.47 mm. The results of the field experimentation show the validity of the proposed method.
Highlights
High-accuracy three-dimensional (3D) measurement for the surfaces of large objects plays a crucial role in evaluating the safe performance of large aviation parts
A large-part measurement method combining with feature compression extraction and directed edge-points criterion is proposed
A sub-pixel centroid extraction method based on compress processing enables the 3D morphology of the measured parts to be accurately reconstructed
Summary
High-accuracy three-dimensional (3D) measurement for the surfaces of large objects plays a crucial role in evaluating the safe performance of large aviation parts. For improving the measurement accuracy, Steger proposed the Hessian matrix method to get the normal directions of stripes in images. Detected the normal directions of the centerline based on the characteristics of the first derivative of the light stripe and located the center points in sub-pixel level along the normal directions by using the pixel subdivision and the centroid of gray method These extraction methods cost much time of computation, and the laser stripe in the image should keep the high quality of Gaussian characteristics. The direct extraction methods based on the geometrical characteristic of laser stripe are mostly adopted by current commercial measurement equipment in the field of aircraft assembly, such as the centroid of gray method (COG), geometric center method and maximum value method.
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