Ma, Y. and Mustapha, F. and Ishak, M.R. and Rahim, S.A. and Mustapha, M. (2022) Data-driven Methods for Damage Detection and Identification of UAV: A Review. Journal of Aeronautics, Astronautics and Aviation, 54 (4). pp. 405-420. ISSN 19907710
Full text not available from this repository.Abstract
Nowadays, UAVs (Unmanned aerial vehicles) have been used widely in various industries. UAVs are normally powered by a rotor installed with the propeller and often operated in complex environments which makes the UAV prone to failure. In order to reduce accidents and improve the reliability of UAVs, a number of methods have been proposed in this paper. Basically, these methods can be divided into model-based methods and data-driven methods. With the emergence of big data analysis, the data-driven method has attracted more and more attention. This method has demonstrated outstanding ability in the field of damage detection and identification. In this paper, a variety of damage detection and identification for UAVs based on data-driven methods are listed and compared. Both advantages and disadvantages of each method are discussed. Furthermore, the application of the data-driven method in other industries is also mentioned in the work. © 2022 The Aeronautical and Astronautical Society of the Republic of China. All rights reserved.
Item Type: | Article |
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Additional Information: | cited By 4 |
Uncontrolled Keywords: | Aircraft detection; Damage detection; Unmanned aerial vehicles (UAV), Aerial vehicle; Complex environments; Damage detection and identification; Data driven; Data-driven methods; Model-based method; Number of methods; Unmanned aerial vehicle, Antennas |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 19 Dec 2023 03:22 |
Last Modified: | 19 Dec 2023 03:22 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/16152 |