Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer

doi:10.1007/s12204-019-2104-4

Abstract

Abstract: A small auto micropipette system is developed to improve the reliability and accuracy of the automatic enzyme immunoassay analyzer’s microscale pipetting system. A sophisticated injection mechanism is designed by the means of dislocation parallel distribution of the screw and injector piston rod. It possesses the function of pipetting, taking and removing the pipette tips. In the control system, STM32 controller is used, controlling the single-axis S-type acceleration/deceleration algorithm and multi-threaded coordinated motion. The acceleration/ deceleration curves are analyzed and optimized by using the method of segmentation; a minimum injection rate of 1 μL and a step rate of 0.05μL are realized. The method of digital image processing is used to detect the amount of pipetting in micro-pipetting quantitatively. The liquid area is extracted by background contrast method, and the liquid volume in the tip is obtained by combining the geometric characteristics of the disposable tip, when the pipetting capacity is not qualified to carry out specific guidance on the pipetting system, and avoid the blocking needle, bubble and other abnormal pipetting phenomenon on the impact of pipetting accuracy. The experimental results show that the combination of the automatic sampling system and the image flow detection system can effectively improve the precision and reliability of the micro-pipetting system. Finally, the injection accuracy of the system at the test points with 10, 50 and 100 μL liquid volumes reaches 1.8%, 1.28% and 1.15% respectively.

Key words: enzyme immunoassay analyzer| micropipette| image processing| motion control| error compensation

摘要： A small auto micropipette system is developed to improve the reliability and accuracy of the automatic enzyme immunoassay analyzer’s microscale pipetting system. A sophisticated injection mechanism is designed by the means of dislocation parallel distribution of the screw and injector piston rod. It possesses the function of pipetting, taking and removing the pipette tips. In the control system, STM32 controller is used, controlling the single-axis S-type acceleration/deceleration algorithm and multi-threaded coordinated motion. The acceleration/ deceleration curves are analyzed and optimized by using the method of segmentation; a minimum injection rate of 1 μL and a step rate of 0.05μL are realized. The method of digital image processing is used to detect the amount of pipetting in micro-pipetting quantitatively. The liquid area is extracted by background contrast method, and the liquid volume in the tip is obtained by combining the geometric characteristics of the disposable tip, when the pipetting capacity is not qualified to carry out specific guidance on the pipetting system, and avoid the blocking needle, bubble and other abnormal pipetting phenomenon on the impact of pipetting accuracy. The experimental results show that the combination of the automatic sampling system and the image flow detection system can effectively improve the precision and reliability of the micro-pipetting system. Finally, the injection accuracy of the system at the test points with 10, 50 and 100 μL liquid volumes reaches 1.8%, 1.28% and 1.15% respectively.

关键词: enzyme immunoassay analyzer| micropipette| image processing| motion control| error compensation

CLC Number:

TP 29
TH 77

SHANG Zhiwu (尚志武), ZHOU Xiangping (周湘平), LI Cheng (李成), ZHOU Xinyu (周昕宇). Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer[J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(5): 605-615.

References 10

[5]	KAPLIT M. Differentiating between abnormal sampleviscosities and pipette clogging during aspiration [J].2011.
[6]	WANG F B, LI Y Y, LIU J, et al. Realization of imageprocess technology for computer vision based onOpenCV [J]. Machinery & Electronics, 2010, 6: 54-57(in Chinese).
[1]	TAO L, LONG W, WANG Y Q. Design and implementationof the control system for an ARM9-basedbiochemical analyzer [J]. Advance Materials Research,2011, 268/269/270: 454-457.
[7]	LIU Z W, SHANG Z W, HUANG Y B. Design of fullautomatic biochemical sampling system [J]. Journal ofEngineering Design, 2016, 23(6): 612-619 (in Chinese).
[2]	WU T Y. Research on high accuracy accumulationtechnology of high speed fully automatic biochemicalanalyzer [D]. Shenzhen: Shenzhen University, Schoolof Health Science Center, 2016 (in Chinese).
[3]	ZHU L Q, ZHANG W C, DONG M L, et al. Methodto improve the micropipette accuracy of full-automaticELISA system [J]. Chinese Journal of Scientific Instrument,2013, 34(5): 1008-1014 (in Chinese).
[8]	HUANG Z B, HUANG Y L, YU S M. Several stepstepper motor acceleration and deceleration method ofcomparative study and its application [J]. Mechanicaland Electrical Engineering, 2011, 28(8): 951-974 (inChinese).
[4]	TAKEDAM, KATOY,KATAGIH. Leakage detectionmethod in automatic pipetting apparatus: EP 1999.
[9]	SHIRONO K, SHIRO M, TANAKA H, et al. Evaluationof “method uncertainty” in the calibration ofpiston pipettes (micropipettes) using the gravimetricmethod in accordance with the procedure of ISO 8655-6 [J]. Accreditation & Quality Assurance, 2014, 19(5):377-389.
[5]	KAPLIT M. Differentiating between abnormal sampleviscosities and pipette clogging during aspiration [J].2011.
[10]	LIU Z G, WAN L C. Error analysis of automatic samplingdevice [J]. Journal of Guangdong PolytechnicNormal University, 2014, 7(3): 38-42 (in Chinese).
[6]	WANG F B, LI Y Y, LIU J, et al. Realization of imageprocess technology for computer vision based onOpenCV [J]. Machinery & Electronics, 2010, 6: 54-57(in Chinese).
[7]	LIU Z W, SHANG Z W, HUANG Y B. Design of fullautomatic biochemical sampling system [J]. Journal ofEngineering Design, 2016, 23(6): 612-619 (in Chinese).
[8]	HUANG Z B, HUANG Y L, YU S M. Several stepstepper motor acceleration and deceleration method ofcomparative study and its application [J]. Mechanicaland Electrical Engineering, 2011, 28(8): 951-974 (inChinese).
[9]	SHIRONO K, SHIRO M, TANAKA H, et al. Evaluationof “method uncertainty” in the calibration ofpiston pipettes (micropipettes) using the gravimetricmethod in accordance with the procedure of ISO 8655-6 [J]. Accreditation & Quality Assurance, 2014, 19(5):377-389.
[10]	LIU Z G, WAN L C. Error analysis of automatic samplingdevice [J]. Journal of Guangdong PolytechnicNormal University, 2014, 7(3): 38-42 (in Chinese).

[1]	SUN Yanyi, FAN Wenjing, ZENG Yuanfan, GAN Xingye, TANG Rijia, HAN Rui. Loading Target Identification Method Based on Harris Corner Detection [J]. Air & Space Defense, 2022, 5(4): 87-91.
[2]	ZHAN Zhu (占竹), ZHANG Wenjun (张文俊), CHEN Xia (陈霞), WANG Jun (汪军) . Objective Evaluation of Fabric Flatness Grade Based on Convolutional Neural Network [J]. J Shanghai Jiaotong Univ Sci, 2021, 26(4): 503-510.
[3]	NIU Mu, XU Liming, ZHAO Da, FAN Fan. Workpiece-Contour-Image Based Wheel Wear Online Detection Methodology [J]. Journal of Shanghai Jiao Tong University, 2021, 55(3): 221-228.
[4]	TAO Zhengrui, DANG Jiaqiang, XU Jinyang, AN Qinglong, CHEN Ming, WANG Li, REN Fei. Eddy Current Distance Measurement Calibration Method for Curved Surface Parts Based on Support Vector Machine Regression [J]. Journal of Shanghai Jiaotong University, 2020, 54(7): 674-681.
[5]	XU Xiaochen, LI Xiang, HUANG Zhong, JU Dehao, LÜ Xingcai, HUANG Zhen. Jet Flame Propagation Characteristics of Methane/Air Mixture in a Large Bore Constant Volume Chamber Based on MATLAB Image Processing Method [J]. Journal of Shanghai Jiaotong University, 2020, 54(5): 490-498.
[6]	LI Yueming,WANG Xiaoping,ZHANG Junjun,CAO Jian,ZHANG Yinghao. X-Rudder Autonomous Underwater Vehicle Control Allocation Based on Improved Quadratic Programming Algorithm [J]. Journal of Shanghai Jiaotong University, 2020, 54(5): 524-531.
[7]	HU Yixing，XU Liming，FAN Fan，ZHANG Zhe. In-Situ Vision Detection and Compensation of Wheel Profile Error in Profile Grinding [J]. Journal of Shanghai Jiaotong University, 2019, 53(6): 654-659.
[8]	ZHU Yeting,ZHU Yanfei,ZHANG Zixin,ZHUANG Qianwei,ZHENG Yifeng. Prediction and Visualization of Crack Width for the Prototype Test on Special-Shaped Shield Segments [J]. Journal of Shanghai Jiaotong University, 2019, 53(10): 1259-1268.
[9]	FENG Wenlong,HUANG Yiqiao,TUO Zhanyu,LI Huimin,YANG Jianguo. Modeling of Thermally Induced Grating Positioning Error of Large Machine Tools Based on Temperature Integral Method [J]. Journal of Shanghai Jiaotong University, 2016, 50(05): 710-715.
[10]	WANG Zhao-yang (王朝阳), LI Hai-bin* (李海滨), WEI Guang-mei (韦广梅). A Research for Error Compensation Algorithm of Dual Range Pressure Sensor [J]. Journal of shanghai Jiaotong University (Science), 2015, 20(3): 370-373.
[11]	LIU Si-yan (刘思妍), LI De-wei* (李德伟), XI Yu-geng (席裕庚), TANG Qi-feng (汤奇峰). A Short-Term Traffic Flow Forecasting Method and Its Applications [J]. Journal of shanghai Jiaotong University (Science), 2015, 20(2): 156-163.
[12]	JING Xu1,QIU Shiguang1,FAN Xiumin1,2,HE Qichang1,2. Tracking Error Compensation of Upper Arm Axial Rotation with Joint DOF Constraint [J]. Journal of Shanghai Jiaotong University, 2014, 48(12): 1667-1674.
[13]	LU Xiang,FENG Zhengping,XU Xuesong. Positioning for Entry Control of Deep-Sea Risers Based on Image Processing [J]. Journal of Shanghai Jiaotong University, 2014, 48(12): 1802-1808.
[14]	WANG Wei,YANG Jianguo. Compound Error Compensation Technique for CNC Machine Tools Based on Interpolation Method [J]. Journal of Shanghai Jiaotong University, 2014, 48(1): 12-21.
[15]	FENG Shao-kong1,2* (冯少孔), HUANG Tao3 (黄涛), LI Hong-jie4 (李宏阶). Automatic Identification of Cracks from Borehole Image Under Complicated Geological Conditions [J]. Journal of shanghai Jiaotong University (Science), 2013, 18(6): 699-705.