Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes
The introduction of computer vision and machine learning into agricultural systems has produced significant new opportunities for high precision application of liquid products in both grain and livestock agriculture. These technologies, which enable liquid application in site-specific, non-broadcast...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | AgriEngineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-7402/5/1/19 |
| _version_ | 1797614075518124032 |
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| author | Benjamin C. Smith Ryan W. Bergman Matthew J. Darr |
| author_facet | Benjamin C. Smith Ryan W. Bergman Matthew J. Darr |
| author_sort | Benjamin C. Smith |
| collection | DOAJ |
| description | The introduction of computer vision and machine learning into agricultural systems has produced significant new opportunities for high precision application of liquid products in both grain and livestock agriculture. These technologies, which enable liquid application in site-specific, non-broadcast applications, are driving new evaluations of nozzle technologies which apply a consistent dose of liquid product in a non-conventional manner compared to historic perceptions. This field of innovation is driving the need for improved high-capacity systems for evaluating nozzle performance in high-precision applications. Historically, patternator tables with volumetric measurements of total applied liquid have served as the standard for fluid nozzle evaluation. These volumetric measurements are based on measuring the displaced distance of liquid over a defined time to determine flow rate. However, current distance sensors present challenges for achieving small-volume measurements and enabling automation at a scale necessary to meet innovation demands of high-precision nozzle systems. A novel concept for high speed and automated measurement of a high precision patternator table was developed using an ultrasonic sensor and a carefully designed liquid retainment system to maximize measurement precision. The performance of this system was quantified by comparing calibrations and performance across different vessels for volume measurement (tubes and pipes) used in the application of a nozzle patternator. A total of three square tubes (15.9, 22.3, 31.0 mm widths) and three pipes (25.2, 27.0, 35.1 mm diameters) were evaluated, with the 27 mm pipe matching the ultrasonic sensor’s rating. All calibrations were successful, depicting linear characteristics with R<sup>2</sup> > 0.99. The smallest pipe presented issues for the sensor to measure in post-calibration and was thus not evaluated further. The residual values from operational performance highlight that the 25.2 mm tube and the 27.0 mm pipe are highly accurate with no indication of bias or non-normality. The relative uncertainty ranges from 2.9 to 42% (350 mL to 25 mL) depending on the tube and pipe cross-sectional diameter or width with the sensor accuracy and uncertainty in the tube and pipe area being the largest factors. The results of this study indicate that the 25.2 mm tube and the 27.0 mm pipe could be excellent options for autonomous liquid volume measurement with the ultrasonic sensor. A key challenge identified in this study is that the assumptions in the sensor’s intrinsic calibration are violated with the tubes and pipes evaluated. |
| first_indexed | 2024-03-11T07:03:32Z |
| format | Article |
| id | doaj.art-75b2277fd52e4c32965e7c0bc61eccc7 |
| institution | Directory Open Access Journal |
| issn | 2624-7402 |
| language | English |
| last_indexed | 2024-03-11T07:03:32Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AgriEngineering |
| spelling | doaj.art-75b2277fd52e4c32965e7c0bc61eccc72023-11-17T09:03:09ZengMDPI AGAgriEngineering2624-74022023-02-015128729810.3390/agriengineering5010019Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and PipesBenjamin C. Smith0Ryan W. Bergman1Matthew J. Darr2Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USADepartment of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USADepartment of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USAThe introduction of computer vision and machine learning into agricultural systems has produced significant new opportunities for high precision application of liquid products in both grain and livestock agriculture. These technologies, which enable liquid application in site-specific, non-broadcast applications, are driving new evaluations of nozzle technologies which apply a consistent dose of liquid product in a non-conventional manner compared to historic perceptions. This field of innovation is driving the need for improved high-capacity systems for evaluating nozzle performance in high-precision applications. Historically, patternator tables with volumetric measurements of total applied liquid have served as the standard for fluid nozzle evaluation. These volumetric measurements are based on measuring the displaced distance of liquid over a defined time to determine flow rate. However, current distance sensors present challenges for achieving small-volume measurements and enabling automation at a scale necessary to meet innovation demands of high-precision nozzle systems. A novel concept for high speed and automated measurement of a high precision patternator table was developed using an ultrasonic sensor and a carefully designed liquid retainment system to maximize measurement precision. The performance of this system was quantified by comparing calibrations and performance across different vessels for volume measurement (tubes and pipes) used in the application of a nozzle patternator. A total of three square tubes (15.9, 22.3, 31.0 mm widths) and three pipes (25.2, 27.0, 35.1 mm diameters) were evaluated, with the 27 mm pipe matching the ultrasonic sensor’s rating. All calibrations were successful, depicting linear characteristics with R<sup>2</sup> > 0.99. The smallest pipe presented issues for the sensor to measure in post-calibration and was thus not evaluated further. The residual values from operational performance highlight that the 25.2 mm tube and the 27.0 mm pipe are highly accurate with no indication of bias or non-normality. The relative uncertainty ranges from 2.9 to 42% (350 mL to 25 mL) depending on the tube and pipe cross-sectional diameter or width with the sensor accuracy and uncertainty in the tube and pipe area being the largest factors. The results of this study indicate that the 25.2 mm tube and the 27.0 mm pipe could be excellent options for autonomous liquid volume measurement with the ultrasonic sensor. A key challenge identified in this study is that the assumptions in the sensor’s intrinsic calibration are violated with the tubes and pipes evaluated.https://www.mdpi.com/2624-7402/5/1/19distance sensingprecision agriculturesprayingultrasonicuncertainty |
| spellingShingle | Benjamin C. Smith Ryan W. Bergman Matthew J. Darr Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes AgriEngineering distance sensing precision agriculture spraying ultrasonic uncertainty |
| title | Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes |
| title_full | Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes |
| title_fullStr | Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes |
| title_full_unstemmed | Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes |
| title_short | Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes |
| title_sort | evaluation of ultrasonic sensor for precision liquid volume measurement in narrow tubes and pipes |
| topic | distance sensing precision agriculture spraying ultrasonic uncertainty |
| url | https://www.mdpi.com/2624-7402/5/1/19 |
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