光学 精密工程, 2015, 23 (11): 3026, 网络出版: 2016-01-25  

利用实时光学图像特征提取法测量液相扩散系数

Measurement of liquid diffusion coefficient by extracting and analyzing features of diffusion images
作者单位
云南大学 物理科学技术学院, 云南 昆明 650091
摘要
介绍了一种利用非对称液芯柱透镜结合实时光学图像特征提取方法测量液相扩散系数(D)的方法。该方法基于图像采集系统的软件开发工具包对采集系统进行二次开发, 并用自编应用软件对图像中特定区域进行亮度及宽度的特征提取。然后, 依据图像特征自动寻找出实验所选液体折射率薄层清晰成像点的位置并记录该位置随时间的变化关系。最后, 根据Fick第二定律计算出液相扩散系数。采用这种方法, 实验研究了室温(25 ℃)条件下乙二醇在纯水中的扩散过程, 测得其扩散系数D=1.164×10-5 cm2/s, 与文献报导值的相对误差为0.34%。与直接观察测量法相比较, 此方法实现了测量的自动化, 避免了人为主观判断误差, 具有测量快速、准确, 计算耗时短, 实验测量结果稳定的特点。
Abstract
A measuring method for liquid diffusion coefficients(D) was proposed by an asymmetric liquid-core cylindrical lens combined with an feature extracting method of optical images in real time automatically. Based on the Software Development Kit provided by a CMOS camera used, the application codes were programmed to extract and analyze the features of the brightness and width of a diffusion image. On the image features, the focal position corresponding to a specific liquid layer with a certain refractive index was found out, and the curve of focal positions varied with diffusion time was recorded automatically. Finally, the diffusion coefficient was calculated by using Ficks second law on the acquired experimental data. With the proposed method, the diffusion process of ethylene glycol with pure water was researched at the room temperature (25 ℃) and the measured diffusion coefficient (D) is 1.164×10-5 cm2/s, the relative error is only 0.34% that of the literature value. As compared with traditional direction observation method, the obtained results demonstrate that the method avoids the error caused by reading focal position with human eye, implements measurement automation and is characterized by higher measuring speeds and accuracy, shorter computing time and stable measuring results.

杨瑞芬, 翟影, 孙丽存, 孟伟东, 普小云. 利用实时光学图像特征提取法测量液相扩散系数[J]. 光学 精密工程, 2015, 23(11): 3026. YANG Rui-fen, ZHAI Ying, SUN Li-cun, MENG Wei-dong, PU Xiao-yun. Measurement of liquid diffusion coefficient by extracting and analyzing features of diffusion images[J]. Optics and Precision Engineering, 2015, 23(11): 3026.

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