| 面向齿廓偏差等精密检测的机器视觉关键技术 |
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| 引用本文： | 葛动元,姚锡凡,向文江,汪海志,刘敏,温学军.面向齿廓偏差等精密检测的机器视觉关键技术[J].机械传动,2019,43(2):171-176. |
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| 作者姓名： | 葛动元 姚锡凡 向文江 汪海志 刘敏 温学军 |
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| 作者单位： | 广西科技大学机械与交通工程学院,广西柳州,545006;华南理工大学机械与汽车工程学院,广东广州,510640;邵阳学院机械与能源工程学院,湖南邵阳,422004;集美大学轮机工程学院,福建厦门,361021 |
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| 基金项目： | 国家自然科学基金;国家自然科学基金;广西自然科学基金 |
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| 摘 要： | 提出一种基于机器视觉的齿廓偏差检测新方法。在求得齿廓过某采样点的法线与基圆的切点后,得到该切点与对应的理论渐开线各离散点组成的各矢量倾角,采用"比较"与"异或"运算,得到过该采样点的齿廓的法线与理论渐开线的交点;然后,在齿轮齿廓渐开线的法线方向上测量齿廓偏差,以确保该方案所得到的齿廓偏差与其定义相一致。经实验得到所测某齿轮的齿廓偏差为6. 944 3μm。实验表明,所提出的基于机器视觉的齿廓偏差的检测方法,能够满足工程精度的需要。
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| 关 键 词： | 机器视觉 渐开线 模数 齿数 齿廓偏差 |
Key Technologies of Machine Vision for Precision Measuring of Profile Deviations |
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| Ge Dongyuan,Yao Xifan,Xiang Wenjiang,Wang Haizhi,Liu Min,Wen Xuejun.Key Technologies of Machine Vision for Precision Measuring of Profile Deviations[J].Journal of Mechanical Transmission,2019,43(2):171-176. |
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| Authors: | Ge Dongyuan Yao Xifan Xiang Wenjiang Wang Haizhi Liu Min Wen Xuejun |
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| Affiliation: | (College of Mechanical and Transportation Engineering,Guangxi University of Science and Technology,Liuzhou 545006,China;School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,China;School of Machine and Energy Engineering,Shaoyang University,Shaoyang 422004,China;School of Marine Engineering,Jimei University,Xiamen 361021,China) |
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| Abstract: | In this paper novel measuring methods for profile deviation are proposed based on machine vision.After the tangent point of the basic circle and the normal line of the tooth profile through a sampled point are obtained,angles of vectors determining by the tangent point and the discrete points of the corresponding theoretical involute are obtained.Then the intersection point between the normal line of the tooth profile through a sampled point and the theoretical involute is obtained by using the operations of "comparison" and "XOR".Finally profile deviations are measured in the normal direction of the profile involute,which makes the tested results be consistent with its definitions.In the experiment,the obtained profile deviation is 6.944 3 μm,which demonstrates the proposed method of profile deviations test based on machine vision can meets the need of precision in engineering practice. |
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| Keywords: | Machine vision Involute Modulus Tooth number Profile deviation |
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