Research on Point Cloud Acquisition and Calibration of Deep Hole Inner Surfaces Based on Collimated Ring Laser Beams

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 17; p. 5790
• Main Authors: Du, Huifu, Zhao, Xiaowei, Yu, Daguo, Shi, Hongyan, Zhou, Ziyang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 06.09.2024
• Subjects: 3D reconstruction; Accuracy; Algorithms; Attitudes; Calibration; Cameras; collimated beam; deep hole detection; Lasers; Light; Methods; point cloud calibration; ring beam; ring beam; deep hole detection; 3D reconstruction; point cloud calibration; collimated beam
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24175790

In this study, a ring light point cloud calibration technique based on collimated laser beams is developed, aiming to reduce errors caused by the position and attitude changes of traditional ring light measurement devices. This article details the generation mechanism of the ring beam and the principle of deep hole measurement. It introduces the collimated beam as a reference, building on traditional ring light measurement devices, to achieve the synchronous acquisition of the ring beam and collimated spot images by an industrial camera. The Steger algorithm is employed to accurately extract the coordinates of the point cloud contours of both the ring beam and the collimated spot. By analyzing the shape and position changes of the collimated spot contour, the spatial position and attitude of the measuring device are precisely determined. This technique is applied to the 3D reconstruction of the inner surface of deep holes, ensuring the accurate restoration of the spatial positional attitude of the ring beam by incorporating the spatial positional attitude parameters of the measuring device to precisely calibrate the cross-sectional point cloud coordinates. Experimental results with ring gauges and deep hole workpieces demonstrate that this technique effectively reduces the percentage of point cloud data outside the tolerance range, and improves the accuracy of the 3D reconstruction model by 6.287%, thereby verifying the accuracy and practicality of this technique.