A Dynamic Detection Method of Capillary Forces Based on Microscopic Vision

doi:10.3969/j.issn.1004-132X.2020.19.004

Abstract

Abstract: For the requirements of real-time detection of capillary forces during the micromanipulation processes, a dynamic detection method of capillary forces was proposed based on microscopic vision. The positioning of microsphere based on Hough transform and the operation tool tracking method by means of the normalized sum-of-squared difference correlation were employed to obtain the real-time location informations. Then, the liquid bridge region of interest was determined. The contour of liquid bridge was extracted by using the terminal identification method of liquid bridge based on Shi-Tomasi corner detection. And, the capillary forces were solved. An experimental setup of capillary force measurement was established based on microscopic vision. The detection processes and detection precision of visual inspection method were discussed. Experimental results indicate that the average detection errors of the dynamic liquid bridge are less than 1.65 μN under a plane-sphere configuration. Parameters including the contact angle and liquid bridge volume may be obtained in real time.

Key words: micromanipulation;microscopic vision, capillary force, liquid bridge, detection

摘要： 针对微操作进程中毛细力实时检测的需求，提出基于显微视觉的毛细力动态检测方法。通过Hough变换的微球对象定位和归一化的平方差相关性的操作工具跟踪方法获取实时位置信息，确定液桥兴趣区域。基于Shi-Tomasi角点检测的液桥端点识别方法提取液桥轮廓，并求解毛细力。搭建显微视觉测量装置，分析检测进程和检测精度。结果表明：平面-球面配置下的动态毛细力的平均检测精度为1.65 μN，且可实时获取接触角、液桥体积等参数。

关键词: 微操作, 显微视觉, 毛细力, 液桥, 检测

CLC Number:

TP241

FAN Zenghua1；RONG Weibin2 ；LIU Zixiao1 ；TIAN Yebing1. A Dynamic Detection Method of Capillary Forces Based on Microscopic Vision[J]. China Mechanical Engineering, DOI: 10.3969/j.issn.1004-132X.2020.19.004.

范增华1;荣伟彬2;刘紫潇1;田业冰1. 基于显微视觉的毛细力动态检测方法[J]. 中国机械工程, DOI: 10.3969/j.issn.1004-132X.2020.19.004.

References

［1］LIANG C, WANG F, SHI B, et al. Design and Control of a Novel Asymmetrical Piezoelectric Actuated Microgripper for Micromanipulation［J］. Sensors and Actuators A: Physical, 2018, 269: 227-237.

［2］CHEN T, SUN L, CHEN L, et al. A Hybrid-type Electrostatically Driven Microgripper with an Integrated Vacuum Tool［J］. Sensors and Actuators A: Physical, 2010, 158(2):320-327.

［3］MONTEIRO P C C, MONTEIRO L, SAVI M A, et al. A Comparative Analysis of Different Shape Memory Alloy Actuator Configurations［J］. Journal of Intelligent Material Systems and Structures, 2017, 28(11):1415-1427.

［4］SOMA A, IAMONI S, VOICU R, et al. Design and Experimental Testing of an Electro-thermal Microgripper for Cell Manipulation［J］. Microsystem Technologies, 2018, 24(2):1053-1060.

［5］RONG W, FAN Z, WANG L, et al. A Vacuum Microgripping Tool with Integrated Vibration Releasing Capability［J］. Review of Scientific Instruments, 2014, 85(8):085002.

［6］VASUDEV A, ZHE J. A Capillary Microgripper Based on Electrowetting［J］. Applied Physics Letters, 2008, 93(10):103503.

［7］VASUDEV A, JAGTIANI A, DU L, et al. A Low-voltage Droplet Microgripper for Micro-object Manipulation［J］. Journal of Micromechanics and Microengineering, 2009, 19(7):75005.

［8］FANTONI G, HANSEN H N, SANTOCHI M. A New Capillary Gripper for Mini and Micro Parts ［J］. CIRP Annals—Manufacturing Technology, 2013, 62(1):17-20.

［9］SAITO S, MOTOKADO T, OBATA K J, et al. Capillary Force with a Concave Probe-tip for Micromanipulation［J］. Applied Physics Letters, 2005, 87(23):234103.

［10］ZHANG Q, WANG H, GAN Y, et al. Method of Orientation Control and Experimental Investigation Using a Liquid-drop Micromanipulator［J］. Journal of Micromechanics and Microengineering, 2017, 27(4):045006.
［11］BHUSHAN B, LING X. Manipulating Microobject by Using Liquid Droplet as a Transporting Vehicle［J］. Journal of Colloid and Interface Science, 2009, 329(1):196-201.
［12］唐君萍, 张丽艳, 刘胜兰, 等. 飞机复杂零件上大量小尺寸导孔的快速视觉检测［J］. 中国机械工程, 2015, 26(18):2456-2465.

TANG Junping, ZHANG Liyan, LIU Shenglan, et al. A Method of Image Perspective Distortion Correction in Ball Pose Detections［J］. China Mechanical Engineering, 2015, 26(18): 2456-2465.

［13］孔明, 贺楚红, 王英军, 等. 基于机器视觉的四通阀自动钎焊定位系统［J］. 中国机械工程, 2016, 27(22):3043-3047.

KONG Ming, HE Chuhong, WANG Yingjun, et al. Four-way Valve Automatic Brazing Positioning System Based on Machine Vision［J］. China Mechanical Engineering,2016, 27(22):3043-3047.

［14］汤勃, 孔建益, 王兴东, 等. 基于图像处理的钢板表面缺陷支持向量机识别［J］. 中国机械工程, 2011, 22(12):1402-1405.

TANG Bo, KONG Jianyi, WANG Xingdong, et al. Steel Surface Defect Recognition Based on Support Vector Machine and Image Processing［J］. China Mechanical Engineering,2011, 22(12): 1402-1405.

［15］KARIMIRAD F, SHIRINZADEH B, YAN W, et al. A Vision-based Methodology to Dynamically Track and Describe Cell Deformation During Cell Micro-manipulation［J］. International Journal of Optomechatronics, 2013, 7(1):33-45.

［16］KASS M, WITKIN A, TERZOPOULOS D. Snakes: Active Contour Models［J］. International Journal of Computer Vision, 1988, 1(4):321-331.

[1]	LIU An-Beng, LIU Ji-Chun. Study on a Large-scale Scanning Three-dimensional Lens Structure of IPC-208B AFM [J]. J4, 201016, 21(16): 1936-1940.
[2]	XU Peng, LIU Bailin, CHEN Yaxiong. Rail Crack Detection Method Based on Differential Flexible Eddy Current Probe [J]. China Mechanical Engineering, 2023, 34(20): 2419-2427.
[3]	YANG Liang, CAI Guixi, LIU Fang, LI Jiankui. Ultrasonic Nondestructive Testing and Evaluation of CFRP Hole-making Structures [J]. China Mechanical Engineering, 2023, 34(19): 2327-2332.
[4]	KE Qingdi, LUO Junyou, JIANG Shouzhi, HUANG Haihong, . Construction of Ultrasonic-Stress Inversion Model Based on Distribution States of Coating Materials [J]. China Mechanical Engineering, 2023, 34(18): 2230-2237.
[5]	HU Bo, LUO Weitao, WANG Shaofei, LAN Xiwang. Quantitative Study on Magnetic Anomaly of Superalloy Surface Defects Based on Parameter Optimization of SVM [J]. China Mechanical Engineering, 2023, 34(17): 2058-2064.
[6]	SUN Yi, LI Changyang, MAO Yalang, YE Weiwei, . In-situ Particle Size Detection Method of Fine Particles Based on Features of Light Scattering Pattern Images [J]. China Mechanical Engineering, 2023, 34(16): 2001-2008.
[7]	LI Xin, CHENG Junsheng, WU Xiaowei, WANG Jian, YANG Yu, . Early Weak Fault Detection Method of Gear Rotating Machinery by Combining SPCA and OCHD [J]. China Mechanical Engineering, 2023, 34(15): 1805-1812.
[8]	HE Qingchuan, LIU Hui, PAN Jun, CHEN Wenhua. Detecting Internal Leakage in Electro-Hydraulic Actuators Based on Operational States of Motor [J]. China Mechanical Engineering, 2023, 34(12): 1407-1414.
[9]	MENG Kang, TENG Wei, PENG Dikang, XIANG Ling, LIU Yibing. Operating Mechanism and Data Driven Approach for Fault Alarm of Wind Turbine Gearbox Systems [J]. China Mechanical Engineering, 2023, 34(12): 1476-1485.
[10]	DU Wenjie, ZHENG Huifeng, ZHANG Kaisheng, TANG Jiaxuan. Research on Far-focused Pixel-based Imaging Method of Defects inside Multilayer Media [J]. China Mechanical Engineering, 2023, 34(09): 1045-1051.
[11]	LIN Xin, ZHANG Jie, FENG Jingyi, MENG Jie, WANG Shuting. Highly Robust Two-stage LiDAR-IMU External Parameter Online Calibration Algorithm [J]. China Mechanical Engineering, 2022, 33(24): 2980-2989.
[12]	JIANG Xuemei, YUAN Zihang, LOU Ping, ZHANG Xiaomei, YAN Junwei, HU Jiwei, . A Collision Detection Method of Heavy-duty CNC Machine Tools Based on Digital Twin [J]. China Mechanical Engineering, 2022, 33(22): 2647-2654，2663.
[13]	LIU Huiyong, ZHANG Song, LI Jianfeng, LUAN Xiaona, . Tool Wear Detection Based on Improved CNN-BiLSTM Model [J]. China Mechanical Engineering, 2022, 33(16): 1940-1947，1956.
[14]	MAN Jia, HUA Zesheng, XIA He, LI Jianyong, LI Fangyi, LI Jianfeng, . Applications of Microfluidic Technology in Cross-domain of Mechanical Engineering and Life Science [J]. China Mechanical Engineering, 2022, 33(15): 1857-1868.
[15]	WANG Ding, WU Deyu, YANG Daliang, CHEN Liting, YE Jinhua, WU Haibin. Air-bag Tactile Sensor with Pressure and Position Detection Functions [J]. China Mechanical Engineering, 2022, 33(14): 1691-1696,1706.