CIESC Journal ›› 2020, Vol. 71 ›› Issue (2): 526-534.DOI: 10.11949/0438-1157.20190738

• Fluid dynamics and transport phenomena • Previous Articles     Next Articles

Microfluidic droplet coalescence study via microscopic image recognition

Hao ZHANG(),Kai WANG()   

  1. Department of Chemical Engineering, State Key Laboratory of Chemical Engineering, Tsinghua University, Beijing 100084, China
  • Received:2019-07-01 Revised:2019-12-04 Online:2020-02-05 Published:2020-02-05
  • Contact: Kai WANG

基于显微图像识别的微流控液滴聚并研究

张皓(),王凯()   

  1. 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
  • 通讯作者: 王凯
  • 作者简介:张皓(1994—),男,硕士研究生,haozhangthu@foxmail.com
  • 基金资助:
    国家自然科学基金面上项目(21776150);全国优秀博士学位论文作者专项(FANEDD 201349)

Abstract:

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.

Key words: microfluidics, coalescence, microscope image analysis, video recognition

摘要:

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。

关键词: 微流控, 聚并, 显微分析, 图像识别

CLC Number: