Data-driven Methods for Damage Detection and Identification of UAV: A Review

• Main Authors: Ma, Y., Mustapha, F., Ishak, M.R., Rahim, S.A., Mustapha, M.
• Format: Article
• Published: The Aeronautical and Astronautical Society of the Republic of China 2022
• Online Access: http://scholars.utp.edu.my/id/eprint/34000/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134880420&doi=10.6125%2fJoAAA.202212_54%284%29.04&partnerID=40&md5=fa53c8e8aa033a1d965b86b7469ddf17

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.