Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer
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 pisto...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Shang, Zhiwu [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of Shanghai Jiaotong University - Cham : Springer Internat. Publ., 1996, 24(2019), 5 vom: 29. Juli, Seite 605-615 |
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| Übergeordnetes Werk: |
volume:24 ; year:2019 ; number:5 ; day:29 ; month:07 ; pages:605-615 |
| Links: |
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| DOI / URN: |
10.1007/s12204-019-2104-4 |
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| Katalog-ID: |
SPR025252437 |
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| 100 | 1 | |a Shang, Zhiwu |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer |
| 264 | 1 | |c 2019 | |
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| 500 | |a © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 | ||
| 520 | |a 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 0.05 μL 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 micropipetting 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. | ||
| 650 | 4 | |a enzyme immunoassay analyzer |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a micropipette |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a image processing |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a motion control |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a error compensation |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Zhou, Xiangping |4 aut | |
| 700 | 1 | |a Li, Cheng |4 aut | |
| 700 | 1 | |a Zhou, Xinyu |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of Shanghai Jiaotong University |d Cham : Springer Internat. Publ., 1996 |g 24(2019), 5 vom: 29. Juli, Seite 605-615 |w (DE-627)669003611 |w (DE-600)2630146-5 |x 1995-8188 |7 nnns |
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| 912 | |a GBV_ILN_2037 | ||
| 912 | |a GBV_ILN_2038 | ||
| 912 | |a GBV_ILN_2039 | ||
| 912 | |a GBV_ILN_2044 | ||
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| 912 | |a GBV_ILN_2064 | ||
| 912 | |a GBV_ILN_2065 | ||
| 912 | |a GBV_ILN_2068 | ||
| 912 | |a GBV_ILN_2070 | ||
| 912 | |a GBV_ILN_2086 | ||
| 912 | |a GBV_ILN_2088 | ||
| 912 | |a GBV_ILN_2093 | ||
| 912 | |a GBV_ILN_2106 | ||
| 912 | |a GBV_ILN_2107 | ||
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| 912 | |a GBV_ILN_2122 | ||
| 912 | |a GBV_ILN_2129 | ||
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| 912 | |a GBV_ILN_2144 | ||
| 912 | |a GBV_ILN_2147 | ||
| 912 | |a GBV_ILN_2148 | ||
| 912 | |a GBV_ILN_2152 | ||
| 912 | |a GBV_ILN_2153 | ||
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10.1007/s12204-019-2104-4 doi (DE-627)SPR025252437 (SPR)s12204-019-2104-4-e DE-627 ger DE-627 rakwb eng Shang, Zhiwu verfasserin aut Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 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 0.05 μL 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 micropipetting 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. enzyme immunoassay analyzer (dpeaa)DE-He213 micropipette (dpeaa)DE-He213 image processing (dpeaa)DE-He213 motion control (dpeaa)DE-He213 error compensation (dpeaa)DE-He213 Zhou, Xiangping aut Li, Cheng aut Zhou, Xinyu aut Enthalten in Journal of Shanghai Jiaotong University Cham : Springer Internat. Publ., 1996 24(2019), 5 vom: 29. Juli, Seite 605-615 (DE-627)669003611 (DE-600)2630146-5 1995-8188 nnns volume:24 year:2019 number:5 day:29 month:07 pages:605-615 https://dx.doi.org/10.1007/s12204-019-2104-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2019 5 29 07 605-615 |
| spelling |
10.1007/s12204-019-2104-4 doi (DE-627)SPR025252437 (SPR)s12204-019-2104-4-e DE-627 ger DE-627 rakwb eng Shang, Zhiwu verfasserin aut Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 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 0.05 μL 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 micropipetting 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. enzyme immunoassay analyzer (dpeaa)DE-He213 micropipette (dpeaa)DE-He213 image processing (dpeaa)DE-He213 motion control (dpeaa)DE-He213 error compensation (dpeaa)DE-He213 Zhou, Xiangping aut Li, Cheng aut Zhou, Xinyu aut Enthalten in Journal of Shanghai Jiaotong University Cham : Springer Internat. Publ., 1996 24(2019), 5 vom: 29. Juli, Seite 605-615 (DE-627)669003611 (DE-600)2630146-5 1995-8188 nnns volume:24 year:2019 number:5 day:29 month:07 pages:605-615 https://dx.doi.org/10.1007/s12204-019-2104-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2019 5 29 07 605-615 |
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10.1007/s12204-019-2104-4 doi (DE-627)SPR025252437 (SPR)s12204-019-2104-4-e DE-627 ger DE-627 rakwb eng Shang, Zhiwu verfasserin aut Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 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 0.05 μL 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 micropipetting 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. enzyme immunoassay analyzer (dpeaa)DE-He213 micropipette (dpeaa)DE-He213 image processing (dpeaa)DE-He213 motion control (dpeaa)DE-He213 error compensation (dpeaa)DE-He213 Zhou, Xiangping aut Li, Cheng aut Zhou, Xinyu aut Enthalten in Journal of Shanghai Jiaotong University Cham : Springer Internat. Publ., 1996 24(2019), 5 vom: 29. Juli, Seite 605-615 (DE-627)669003611 (DE-600)2630146-5 1995-8188 nnns volume:24 year:2019 number:5 day:29 month:07 pages:605-615 https://dx.doi.org/10.1007/s12204-019-2104-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2019 5 29 07 605-615 |
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10.1007/s12204-019-2104-4 doi (DE-627)SPR025252437 (SPR)s12204-019-2104-4-e DE-627 ger DE-627 rakwb eng Shang, Zhiwu verfasserin aut Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 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 0.05 μL 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 micropipetting 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. enzyme immunoassay analyzer (dpeaa)DE-He213 micropipette (dpeaa)DE-He213 image processing (dpeaa)DE-He213 motion control (dpeaa)DE-He213 error compensation (dpeaa)DE-He213 Zhou, Xiangping aut Li, Cheng aut Zhou, Xinyu aut Enthalten in Journal of Shanghai Jiaotong University Cham : Springer Internat. Publ., 1996 24(2019), 5 vom: 29. Juli, Seite 605-615 (DE-627)669003611 (DE-600)2630146-5 1995-8188 nnns volume:24 year:2019 number:5 day:29 month:07 pages:605-615 https://dx.doi.org/10.1007/s12204-019-2104-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2019 5 29 07 605-615 |
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10.1007/s12204-019-2104-4 doi (DE-627)SPR025252437 (SPR)s12204-019-2104-4-e DE-627 ger DE-627 rakwb eng Shang, Zhiwu verfasserin aut Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 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 0.05 μL 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 micropipetting 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. enzyme immunoassay analyzer (dpeaa)DE-He213 micropipette (dpeaa)DE-He213 image processing (dpeaa)DE-He213 motion control (dpeaa)DE-He213 error compensation (dpeaa)DE-He213 Zhou, Xiangping aut Li, Cheng aut Zhou, Xinyu aut Enthalten in Journal of Shanghai Jiaotong University Cham : Springer Internat. Publ., 1996 24(2019), 5 vom: 29. Juli, Seite 605-615 (DE-627)669003611 (DE-600)2630146-5 1995-8188 nnns volume:24 year:2019 number:5 day:29 month:07 pages:605-615 https://dx.doi.org/10.1007/s12204-019-2104-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2019 5 29 07 605-615 |
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Shang, Zhiwu @@aut@@ Zhou, Xiangping @@aut@@ Li, Cheng @@aut@@ Zhou, Xinyu @@aut@@ |
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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 0.05 μL 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 micropipetting system. 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Shang, Zhiwu |
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Shang, Zhiwu misc enzyme immunoassay analyzer misc micropipette misc image processing misc motion control misc error compensation Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer |
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Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer enzyme immunoassay analyzer (dpeaa)DE-He213 micropipette (dpeaa)DE-He213 image processing (dpeaa)DE-He213 motion control (dpeaa)DE-He213 error compensation (dpeaa)DE-He213 |
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design of micropipette system with high precision for small enzyme immunoassay analyzer |
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Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer |
| 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 0.05 μL 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 micropipetting 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. © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
| abstractGer |
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 0.05 μL 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 micropipetting 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. © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
| abstract_unstemmed |
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 0.05 μL 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 micropipetting 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. © Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
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Design of Micropipette System with High Precision for Small Enzyme Immunoassay Analyzer |
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https://dx.doi.org/10.1007/s12204-019-2104-4 |
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Zhou, Xiangping Li, Cheng Zhou, Xinyu |
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10.1007/s12204-019-2104-4 |
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| score |
7.4008465 |