基于点云数据的同步带齿廓参数测量研究。

Research on Measurement of Tooth Profile Parameters of Synchronous Belt Based on Point Cloud Data.

机构信息

School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou 310012, China.

出版信息

Sensors (Basel). 2022 Aug 24;22(17):6372. doi: 10.3390/s22176372.

DOI:10.3390/s22176372

PMID:36080833

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9460103/

Abstract

Accurately detecting the tooth profile parameters of the synchronous belt is crucial for the transmission's load distribution and service life. However, the existing detection methods have low efficiency, are greatly affected by the manual experience, and cannot realize automatic detection. A measurement method based on point cloud data is proposed to solve this issue. The surface space points of the synchronous belt are acquired by a line-structured light sensor, and the raw point clouds are preprocessed to remove outliers and reduce the number of points. Then, the point clouds are divided into plane and arc regions, and different methods are used for fitting. Finally, the parameters of each tooth are calculated. The experimental results show that the method has high measurement accuracy and reliable stability and can replace the original detection method to realize automatic detection.

摘要

准确检测同步带的齿廓参数对于传动的负载分布和使用寿命至关重要。然而，现有的检测方法效率低下，受人工经验影响较大，无法实现自动检测。提出了一种基于点云数据的测量方法来解决这个问题。使用线结构光传感器获取同步带的表面空间点，对点云进行预处理，以去除离群点并减少点数。然后，将点云分为平面和弧形区域，并使用不同的方法进行拟合。最后，计算每个齿的参数。实验结果表明，该方法具有较高的测量精度和可靠的稳定性，可以替代原有的检测方法实现自动检测。