Integration of Discrete Wavelet and Fast Fourier Transforms for Quadcopter Fault Diagnosis

Due to the extensive use of Unmanned Aerial Vehicles (UAVs) and the co-evolution of current technology, a key introduction to fault detection has arisen in recent studies in order to prevent unfortunate consequences. In this study, vibration-based signals from a commercially available innovative quadcopter flying in hover mode are collected using a vibration accelerometer, a data acquisition device, and a laptop. An ADXL335 accelerometer is fixed on the center of the drone where the centerlines of the four blades intersect. The superposition of numerous vibration arrangements over identical spectra hinders the ability to analyze the spectral data in the manner required to locate any framework's discrete vibration. This work presents a technique for separating a synthesized vibration signal towards discrete vibrations and other extraneous vibrations of a structure utilizing the Discrete Wavelet Transform (DWT) integrated with the Fast Fourier Transform (FFT). The research article findings in this study demonstrate the reliability and applicability of specific categories of discrete vibrations that are sorted out during the structural change evaluation to develop the best feasible strategy for removing the undesired and unanticipated vibration components and noise. The methodology demonstrated in this paper has the potential for practical application to multirotor UAVs in general.