清华大学化学工程系,化学工程联合国家重点实验室,北京 100084
张皓(1994—),男,硕士研究生,haozhangthu@foxmail.com
王凯(1983—),男,博士,副教授,kaiwang@tsinghua.edu.cn
收稿:2019-07-01,
修回:2019-12-04,
网络首发:2020-08-14,
纸质出版:2020-02-05
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张皓, 王凯. 基于显微图像识别的微流控液滴聚并研究[J]. 化工学报, 2020, 71(2): 526-534
ZHANG Hao, WANG Kai. Microfluidic droplet coalescence study via microscopic image recognition[J]. CIESC Journal, 2020, 71(2): 526-534
张皓, 王凯. 基于显微图像识别的微流控液滴聚并研究[J]. 化工学报, 2020, 71(2): 526-534 DOI: 10.11949/0438-1157.20190738.
ZHANG Hao, WANG Kai. Microfluidic droplet coalescence study via microscopic image recognition[J]. CIESC Journal, 2020, 71(2): 526-534 DOI: 10.11949/0438-1157.20190738.
微流控技术作为操控微米尺度液滴的重要手段,受到普遍关注。显微摄像是微流控过程的主要研究方法,以往主要通过人工观察识别的方式获取关键参数,工作效率低、数据量小,限制了针对复杂微流控过程的深入认识。提出了一种基于MATLAB图像处理程序的微流控液滴聚并研究方法,通过背景提取、背景扣除、掩膜二值化、噪声消除、区域填充、形态开启、边界物体移除、干扰滤除等过程,实现六边形扩大通道内液滴聚并显微实验视频的数值化,进一步通过识别液滴投影面积、质心、偏心率等信息,研究了液滴运动速度和液膜的排空时间等微流控聚并关键参数的变化规律。
Microfluidic technology
as an important approach of manipulating micrometer-scale droplets
has received widespread attention. Microscope recording is the main research method of micro-fluidic process. In the past
key parameters were mainly obtained through manual observation and identification. The low efficiency and small amount of data limited the in-depth understanding of complex micro-fluidic processes. This paper proposes a method to studying microfluidic droplet coalescence based on MATLAB image processing program with background extraction
background subtraction
mask binarization
noise elimination
region filling
shape opening
boundary object removal
interference filtering and
etc
.
which digitized the microscopic videos experimentally collected in a hexagonal microchannel. Furthermore
by identifying the droplet projection area
centroid
eccentricity and other information
the key parameters of microfluidic processes
including droplet speed and liquid film drainage time are also studied.
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