为了提高机器视觉螺纹的测量精度，建立了基于螺纹图像质量的评价方法。通过对螺纹灰度图像的行灰度分布情况和螺纹光学成像特点的分析，揭示出由于螺旋升角造成螺纹图像牙廓边缘失真的机理。在分析多种螺纹图像评价方法性能的基础上，采用基于螺纹边缘的评价算法L-yakuo，计算多幅不同物距螺纹图像的评价值。最后，通过对机器视觉求取的M14×2、M20×2.5牙型角和接触测量仪得到的牙型角进行实验对比分析。实验结果表明：采用L-yakuo算法得到最清晰的牙廓图像后再进行机器视觉螺纹牙型角求取，规格M14×2、M20×2.5的螺纹牙型角精度平均提高
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。借助L-yakuo算法能够灵敏地反映螺纹牙廓清晰度，基本满足了螺纹图像清晰度的评价需求，评价值的变化和牙型角相对误差的变化基本一致，且该评价值具有精度高、易计算的特点。
Abstract
In order to improve the measurement accuracy of machine vision thread, an evaluation method based on thread image quality was established. Through the analysis of the line gray-level distribution of the thread gray images and the optical imaging characteristics of the thread, the mechanism of the thread image edge distortion caused by the helix angle was revealed. Based on the analysis of the performance of various thread image evaluation methods, the evaluation algorithm L-yakuo based on the thread edge was adopted to calculate the evaluation value of multiple thread images with different object distances. Finally, the experimental comparison and analysis of the M14×2, M20×2.5 thread angle obtained by machine vision and the thread angle obtained by contact measuring instrument were carried out. The experimental results show that after the clearest tooth profile image is obtained by the L-yakuo algorithm, the machine vision thread angle is calculated, and the accuracy of the thread angle of M14×2 and M20×2.5 is improved
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on average. With the help of L-yakuo algorithm, it can sensitively reflect the definition of thread profile, which basically meets the evaluation requirements of thread image definition. The changes of the evaluation value are basically the same as the changes of the relative error of the thread angle, and the evaluation value has the characteristics of high accuracy and easy to calculate.
关键词
螺旋升角 /
牙廓失真 /
清晰度评价值 /
牙型角 /
机器视觉
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Key words
machine vision /
helix angle /
thread profile distortion /
definition evaluation value /
thread angle
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