A Method for Measuring Shaft Diameter Based on Light Stripe Image Enhancement
Author:
Li Chunfeng12, Xu Xiping1, Liu Siyuan3, Ren Zhen4
Affiliation:
1. College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China 2. School of Electronic Information Engineering, Changchun University, Changchun 130022, China 3. School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China 4. College of Mechanical and Vehicle Engineering, Changchun University, Changchun 130022, China
Abstract
When the workpiece surface exhibits strong reflectivity, it becomes challenging to obtain accurate key measurements using non-contact, visual measurement techniques due to poor image quality. In this paper, we propose a high-precision measurement method shaft diameter based on an enhanced quality stripe image. By capturing two stripe images with different exposure times, we leverage their different characteristics. The results extracted from the low-exposure image are used to perform grayscale correction on the high-exposure image, improving the distribution of stripe grayscale and resulting in more accurate extraction results for the center points. The incorporation of different measurement positions and angles further enhanced measurement precision and robustness. Additionally, ellipse fitting is employed to derive shaft diameter. This method was applied to the profiles of different cross-sections and angles within the same shaft segment. To reduce the shape error of the shaft measurement, the average of these measurements was taken as the estimate of the average diameter for the shaft segment. In the experiments, the average shaft diameters determined by averaging elliptical estimations were compared with shaft diameters obtained using a coordinate measuring machine (CMM) the maximum error and the minimum error were respectively 18 μm and 7 μm; the average error was 11 μm; and the root mean squared error of the multiple measurement results was 10.98 μm. The measurement accuracy achieved is six times higher than that obtained from the unprocessed stripe images.
Funder
National Natural Science Foundation of China Jilin Province Science and Technology Development Plan Project
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