Vibration-Based Fault Detection in Drone using Artificial Intelligence

Recent years have seen a huge increase in the study of drones. There is a lot of published articles regarding drone, focusing on control optimization, fault detection, safety mechanisms, etc. In fault detection, most of the studies focused on the effects of faulty propellers and rotors, and there is very limited academic research on drone arms. In this paper, a fault detection based on the vibration of the multirotor arms using artificial intelligence (AI) is proposed. There are some cases where due to an accident, the arm
of the multirotor crack or loose. This is normally unnoticeable without disassembly and if not taken care of, it would have likely resulted in a sudden loss of flight stability, which will lead to a crash.

Two types of AI methods are incorporated in this study, namely, fuzzy logic and neuro-fuzzy, using the fuzzy logic and ANFIS toolbox in the MATLAB software, respectively. For the neuro-fuzzy approach, we use 100 and 1000 datasets to determine the effects of the ...