中文版 | English
Title

Estimation of Airflow Parameters for Tail-Sitter UAV through a 5-Hole Probe Based on an ANN

Author
Corresponding AuthorWu, Yongliang
Publication Years
2023-01
DOI
Source Title
ISSN
1424-8220
Volume23
Abstract
Fixed-wing vertical take-off and landing (VTOL) UAVs have received more and more attention in recent years, because they have the advantages of both fixed-wing UAVs and rotary-wing UAVs. To meet its large flight envelope, the VTOL UAV needs accurate measurement of airflow parameters, including angle of attack, sideslip angle and speed of incoming flow, in a larger range of angle of attack. However, the traditional devices for the measurement of airflow parameters are unsuitable for large-angle measurement. In addition, their performance is unsatisfactory when the UAV is at low speed. Therefore, for tail-sitter VTOL UAVs, we used a 5-hole pressure probe to measure the pressure of these holes and transformed the pressure data into the airflow parameters required in the flight process using an artificial neural network (ANN) method. Through a series of comparative experiments, we achieved a high-performance neural network. Through the processing and analysis of wind-tunnel-experiment data, we verified the feasibility of the method proposed in this paper, which can make more accurate estimates of airflow parameters within a certain range.
© 2022 by the authors.
Indexed By
EI ; SCI
Language
English
SUSTech Authorship
First
Funding Project
This research was funded by Xuanyun-SUSTech School of Innovation and Entrepreneurship Joint Laboratory of eVTOL Intelligent Hybrid Electric Propulsion Technology, (Grant number K2242Z055).
WOS Accession No
WOS:000909982700001
Publisher
EI Accession Number
20230213373476
EI Keywords
Aircraft landing ; Angle of attack ; Angle of attack indicators ; Fixed wings ; Flight envelopes ; Parameter estimation ; Probes ; Unmanned aerial vehicles (UAV) ; VTOL/STOL aircraft ; Wind tunnels
ESI Classification Code
Aerodynamics, General:651.1 ; Wind Tunnels:651.2 ; Aircraft, General:652.1 ; Aircraft Instruments and Equipment:652.3
ESI Research Field
CHEMISTRY
Data Source
EV Compendex
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/519645
DepartmentDepartment of Mechanics and Aerospace Engineering
工学院
创新创业学院
Affiliation
1.Department of Mechanics and Aerospace Engineering, College of Engineering, Southern University of Science and Technology, Shenzhen; 518055, China
2.School of Aeronautics and Astronautics, Xihua University, Chengdu; 610039, China
3.College of Innovation and Entrepreneurship, Southern University of Science and Technology, Shenzhen; 518055, China
4.School of Physics and Mechatronics Engineering, Longyan University, Longyan; 364012, China
First Author AffilicationDepartment of Mechanics and Aerospace Engineering;  College of Engineering
First Author's First AffilicationDepartment of Mechanics and Aerospace Engineering;  College of Engineering
Recommended Citation
GB/T 7714
Li, Xiaoda,Wu, Yongliang,Shan, Xiaowen,et al. Estimation of Airflow Parameters for Tail-Sitter UAV through a 5-Hole Probe Based on an ANN[J]. SENSORS,2023,23.
APA
Li, Xiaoda,Wu, Yongliang,Shan, Xiaowen,Zhang, Haofan,&Chen, Yang.(2023).Estimation of Airflow Parameters for Tail-Sitter UAV through a 5-Hole Probe Based on an ANN.SENSORS,23.
MLA
Li, Xiaoda,et al."Estimation of Airflow Parameters for Tail-Sitter UAV through a 5-Hole Probe Based on an ANN".SENSORS 23(2023).
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