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Detection of unbalanced blade on UAV by means of audio signal

The use of drones in several areas such as agriculture, security, cinema, sports, enjoyment, and rescue task, to name a few, has grown considerably in recent years. Likewise, the use of drones with autonomous flight is common nowadays. During the drone’s flight, especially autonomous flight in forest, the blades of the rotor may be damaged, scratched or bent due to a collision with a branch or object. These types of mishap can cause the blade to become unbalanced, causing the drone to oscillate or, in the worst case, fall, causing further damage. Taking these into account, in this paper a detection of unbalanced blade on a quadrotor UAV by means of sound is proposed. Sound signals are acquired during the takeoff and hovering, then analyzed using DWT decomposition and Fourier Transform. The tests were performed using a balanced blade and an artificially unbalanced blade (to simulated a damage). The results show that the proposed methodology is able to distinguish between a balanced and unbalanced blade.