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Ultrasonic sensor for UAV flight navigation

Vagapov, Yuriy, Bolam, Robert, Davies, David Gareth and Excell, Peter S (2018) Ultrasonic sensor for UAV flight navigation. In: 2018 25th International Workshop on Electric Drives: Optimization in Control of Electric Drives (IWED), 31 Jan - 2 Feb 2018, Moscow Power Engineering Institute, Moscow, Russia.

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Official URL: http://ieeexplore.ieee.org/document/8321389/

Abstract

Ultrasonic transducers were utilized for the design and development of an alternative method for flight instrumentation measurement of the velocity of unmanned air vehicles (UAVs). Current methods have been deemed to have significant shortcomings, such as the need for GPS thus leading to indoor UAV operations being incapable of velocity sensing. The proposed concept is developed from the utilization of ultrasonic transit-time flowmeters. A test bench has been produced to measure the accuracy and confirm the validity of the concept. Two key design variables were determined - the optimal transducer mounting configuration and the optimal angle of incidence for the transducer mountings. The mounting configurations were analyzed from common transit-time flowmeter sensor configurations and were tested using both CFD and acoustic simulations. The findings are presented and correlated based on these simulations and it was determined that a V-method configuration was the optimal choice. The correct angle of incidence was determined by an experimental methodology. The time-of-flight outputted from the transducers was compared to the calculated ideal value, and the findings revealed that an angle of 30° was the most accurate for the reflection of the emitted wave. The experimentation was conducted with a specially designed test bench and associated electronic hardware located in a wind tunnel. The test results have provided conclusive evidence that the overall design can produce accurate results comparable with current instrumentation sensors.

Item Type: Conference or Workshop Item (Paper)
Divisions: Applied Science, Computing and Engineering
Depositing User: Hayley Dennis
Date Deposited: 09 May 2018 09:58
Last Modified: 09 May 2018 09:58
URI: http://glyndwr.collections.crest.ac.uk/id/eprint/17297

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