In the field of industrial measurement, structured light technique, as a non-contact, efficient, and high-precision active measurement method, has been widely applied in industrial inspection. Turbine blades are critical components of aero engines, and their surface shape directly affect the performance and lifespan of the equipment. Therefore, accurately measuring their surfaces is of significant research importance. This paper aims to construct a binocular structured light measurement system to meet the high-precision and high-efficiency detection requirements of turbine blades. This study adopts a 12-step phase-shifting and complementary Gray code technique and utilizes binocular reconstruction techniques to obtain three-dimensional point cloud data of the blade surface. Experimental results demonstrate that this measurement system can quickly acquire high-resolution three-dimensional surface data of turbine blades. Compared with traditional contact measurement methods, it has advantages such as non-contact operation, rapidity, and high precision. The accuracy and reliability of this method are verified through measurements on standard spheres and comparisons with theoretical models of the blades. This research provides an efficient and reliable solution for surface detection of turbine blades in the industrial domain, which is of great significance for improving the manufacturing quality and operational performance of turbine equipment.
Structural light measurement as a non-contact measurement method is commonly used in 3D shape detection, which can quickly acquire large-scale points cloud data of 3D surface with high precision. In the development of triangulation structural light sensors, the extraction of the light stripe centerline is the most important research point. Aiming at the problems of large error, high computational complexity and low data processing efficiency in the traditional maximum value based centerline extraction methods, a novel centerline extraction method based on actual light intensity distribution is proposed. Compared with the center line extraction method based on normal direction of light stripe, the discussed method is more suitable to describe the spatial characteristics of light stripe energy structure. It can greatly reduce the amount of calculation, improve processing speed and accuracy. The effectiveness of the proposed method is verified by a practical case of structural light sensor development.
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