Ultrasonic Sensor for UAV Flight Navigation

被引:9
作者
Davies, David Gareth [1 ]
Bolam, Robert Cameron [1 ]
Vagapov, Yuriy [1 ]
Excell, Peter [1 ]
机构
[1] Glyndwr Univ, Sch Appl Sci Comp & Engn, Mold Rd, Wrexham LL11 2AW, Wales
来源
2018 25TH INTERNATIONAL WORKSHOP ON ELECTRIC DRIVES: OPTIMIZATION IN CONTROL OF ELECTRIC DRIVES (IWED2018) | 2018年
关键词
drone; UAS; unmanned air vehicle; ultrasonic guidance system; sensor technology; ultrasonic flight navigation;
D O I
10.1109/IWED.2018.8321389
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Ultrasonic transducers were utilised 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 utilisation 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 analysed 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 degrees 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.
引用
收藏
页数:7
相关论文
共 15 条
[1]  
Bragg M., 2015, FLOW CONTROL, V21, P22
[2]  
Czichy R. H., 1995, SENSORS MICRO NANOSE, V8, P365
[3]  
Flow Control Staff, 2016, FLOW CONTROL, V22, P6
[4]  
Gebre-Egziabher D., 2000, IEEE 2000. Position Location and Navigation Symposium (Cat. No.00CH37062), P185, DOI 10.1109/PLANS.2000.838301
[5]  
Greenspan R. L., 1995, Navigation. Journal of the Institute of Navigation, V42, P165
[6]  
Haiyang Chao, 2010, 2010 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2010), P211, DOI 10.1109/MFI.2010.5604460
[7]  
MarketsAndMarkets, 2017, UAV MARK WORTH 28 27
[8]   COLIBRI: A vision-guided UAV for surveillance and visual inspection [J].
Mejias, Luis ;
Correa, Juan F. ;
Mondragon, Ivan ;
Campoy, Pascual .
PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-10, 2007, :2760-+
[9]   THE PERIGEO PROJECT: INERTIAL AND IMAGING SENSORS PROCESSING, INTEGRATION AND VALIDATION ON UAV PLATFORMS FOR SPACE NAVIGATION [J].
Molina, P. ;
Angelats, E. ;
Colomina, I. ;
Latorre, A. ;
Montao, J. ;
Wis, M. .
EUROPEAN CALIBRATION AND ORIENTATION WORKSHOP (EUROCOW 2014), 2014, :79-85
[10]   Automatic Noninvasive Measurement of Arterial Blood Pressure [J].
Nitzan, Meir .
IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE, 2011, 14 (01) :32-37