@article{scholars16152, pages = {405--420}, publisher = {The Aeronautical and Astronautical Society of the Republic of China}, journal = {Journal of Aeronautics, Astronautics and Aviation}, year = {2022}, title = {Data-driven Methods for Damage Detection and Identification of UAV: A Review}, doi = {10.6125/JoAAA.20221254(4).04}, note = {cited By 4}, volume = {54}, number = {4}, author = {Ma, Y. and Mustapha, F. and Ishak, M. R. and Rahim, S. A. and Mustapha, M.}, issn = {19907710}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134880420&doi=10.6125\%2fJoAAA.202212\%5f54\%284\%29.04&partnerID=40&md5=fa53c8e8aa033a1d965b86b7469ddf17}, 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}, 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. {\^A}{\copyright} 2022 The Aeronautical and Astronautical Society of the Republic of China. All rights reserved.} }