Detecção de Falhas em Drones através da Análise de Sinais baseada no Caos utilizando a Amplitude de Picos (SAC-AM)

Abstract

Unmanned aerial vehicles (UAVs) are widely used in various fields for different purposes and objectives, and with their growing and extensive expansion, the emergence of defects becomes inevitable, whether due to the wear of their components or related to improper use. This work aimed to implement an algorithm for the classification and identification of faults using data from accelerometers through the technique of Signal Analysis based on Chaos using Peak Amplitude (SAC-AM), as well as the validation of the technique. The results achieved demonstrated that the algorithm is capable of satisfactorily distinguishing the nuances between flight scenarios that represent faults or the absence thereof.