Zhu Yanlong, Cheng Yinbao, Gao Hongtang, Sun Shuanghua, Zhang Xudong, Xue Liang, Tang Jiangwen, Tang Yingqi
College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou 310018, China.
Division of Dimensional Metrology, National Institute of Metrology, Beijing 100029, China.
Micromachines (Basel). 2024 Sep 17;15(9):1162. doi: 10.3390/mi15091162.
Currently, there are various types of microscales and the conventional line detection system usually has only one detection method, which is difficult to adapt to the diverse calibration needs of microscales. This article investigates the high-precision measurement method of a microscale based on optoelectronics and the image integration method to solve the diversified calibration needs of microscales. The automatic measurement and processing system integrates two methods: the photoelectric signal measurement method and the photoelectric image measurement method. This article studies the smooth motion method based on ordinary linear guides, investigates the method of reducing the cosine error of a small-range interference length measurement, proposes an image-based line positioning method, and studies the edge and center recognition algorithms of the line. According to the experimental data, the system's measurement accuracy was analyzed using the photoelectric signal measurement method to measure the 1 mm microscale, the maximum difference from the reference value was 0.105 μm, the standard uncertainty was 0.068 μm, and the absolute value of normalized error was less than 1. The accuracy of the image measurement method to measure the 1 mm microscale was consistent with that of the photoelectric signal method. The results show good consistency in the measurement results between the two methods of the integrated measurement system. The photoelectric signal method has the technical characteristics of high measurement efficiency and high accuracy, while the pixel-based measurement of the image method has two-dimensional measurement characteristics, which can realize measurements that cannot be realized by the photoelectric signal method; therefore, the measurement system of optoelectronics and image integration is characterized by high precision and a wide range of measurement adaptations.
目前，微尺度的类型多种多样，而传统的线检测系统通常只有一种检测方法，难以适应微尺度多样化的校准需求。本文研究基于光电和图像积分方法的微尺度高精度测量方法，以解决微尺度的多样化校准需求。自动测量与处理系统集成了两种方法：光电信号测量方法和光电图像测量方法。本文研究基于普通直线导轨的平滑运动方法，研究减小小范围干涉长度测量余弦误差的方法，提出基于图像的线定位方法，并研究线的边缘和中心识别算法。根据实验数据，采用光电信号测量方法测量1mm微尺度时，分析了系统的测量精度，与参考值的最大差值为0.105μm，标准不确定度为0.068μm，归一化误差绝对值小于1。图像测量方法测量1mm微尺度的精度与光电信号方法一致。结果表明，集成测量系统的两种方法在测量结果上具有良好的一致性。光电信号法具有测量效率高、精度高的技术特点，而图像法基于像素的测量具有二维测量特性，能够实现光电信号法无法实现的测量；因此，光电与图像集成测量系统具有高精度和测量适应性广的特点。
