考虑显微光学涉及的聚焦精度对机器视觉精密测量效果的影响, 开展了显微视觉环境下对图像聚焦技术综合定量评价的研究。建立了偏移率等系列性能指标, 对13组清晰度函数在显微视觉条件下的无偏性、单峰性、分辨力等进行了综合评价, 优选出方差函数和Brenner函数分别用于粗聚焦和精聚焦阶段的清晰度计算。建立了分步爬山搜索法, 实现了显微自动聚焦。与传统爬山法相比, 提出的方法聚焦时间显著缩短, 重复精度提高约24%。将建立的自动聚焦与图像测量方法应用于某电液伺服阀衔铁气隙测量中, 得到的测量均值与工具显微镜结果相近, 而测量标准差可达1.9 μm, 测量效率也显著提高。最后对伺服阀加电条件下的气隙动力学特性进行了测试, 获得了驱动电流-衔铁气隙之间的关系, 为在线装配/装调提供了重要依据。

The auto-focusing precision of microscopy has great influence on the performance of machine-vision-based precise measurement. A comprehensively quantitative evaluation method on image auto-focusing technique in a microscopic vision environment was researched. Several kinds of evaluation indexes were proposed, and the unbiasedness, unimodality, spatial resolution etc. of 13 groups sharpness functions were comprehensively evaluated in a microscopic vision condition. Then variance function and Brenner function were chosen to calculate the sharpness functions in coarse and fine focusing processes respectively. A modified Mountain Climbing Searching (MCS) algorithm was proposed to implement the micro-automatic focusing. As comparing to common MCS method, the modified method significantly improves the time consuming and increases the repeatability by about 24%. Finally, the developed auto-focusing algorithm was integrated into the system and was applied to the measurement of armature gap in a servo solenoid valve. The results show that the standard deviation of measurement is 1.9 μm, the precision is similar to that of the universal tool microscope, and the efficiency is significantly improved. Moreover, the system was also utilized for dynamic characteristic detection of gaps in the solenoid valve under the condition of power up, the relation between driving current and armature gap is obtained, which provides a reliable evidence for in-situ micro-assembly.