Date of Award:
12-2024
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Electrical and Computer Engineering
Committee Chair(s)
Sierra Young
Committee
Sierra Young
Committee
Calvin Coopmans
Committee
Burak Sarsilmaz
Abstract
Aquaculture farms, like oyster farms, often use outdated techniques to measure the quality of their waters. These techniques are often stationary or are deployed by an operator who may struggle to reach a location depending on conditions like the presence of a storm or low tide. This creates data sets with gaps over time and across the area of the farm, meaning the data cannot be used to model the standard farm conditions. An Uncrewed Aerial System (UAS) payload is developed in this paper that is capable of measuring depth-velocity profiles through the use of a tethered velocity sensor. The tether is able to detach from the UAS through a magnetic release to ensure UAS safety. Controlled water flumes helped in the reverse-engineering of the sensor's communication protocol. Tests in irrigation canals demonstrate the payload's ability to measure in place of the traditional datalogger with less than 3% mean error. The payload was able to successfully measure the velocity of a coastal water channel when deployed from a bridge with less than 2% mean error. The payload was able to be deployed on a UAS in under 15 minutes by one person, which is much faster than other water velocity measurement methods. The payload was able to measure around 10 locations per flight and was moderately successful at measuring the depth-velocity profile of the locations. When the sensor was properly aligned in the direction of the water flow, the sensor had mean errors as low as 4%. However, misalignment and low sample count caused other locations to have errors as high as 31%. Low sample count is easily solved through the use of better depth control and longer sampling times. Future work needs to be done on sensor orientation control to limit that source of error.
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Recommended Citation
Bailey, Mitchell, "Development of a Subsurface Water Velocity and Quality Measurement Payload for sUAS" (2024). All Graduate Theses and Dissertations, Fall 2023 to Present. 362.
https://digitalcommons.usu.edu/etd2023/362
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