Monitoring mechanical vibration is crucial for ensuring the structural integrity and optimal performance of unmanned aerial vehicles (UAVs). This study introduces a portable and low-cost system that enables integrated acquisition and analysis of UAV vibration data in a single step, using a Raspberry Pi 4B, data acquisition (DAQ) through a MCC128 DAQ HAT card, and six accelerometers positioned at strategic structural points. Ground-based engine tests at 2700 RPM allowed vibration data to be recorded under conditions similar to those of real operation. Data was processed with a Kalman filter, a Hann window function application, and frequency analysis via Fast Fourier Transform (FFT). The first and second wing bending natural frequencies were identified at 12.3 Hz and 17.5 Hz, respectively, as well as a significant component around 23 Hz, which is a subharmonic of the propulsion system excitation frequency near 45 Hz. The results indicate that the highest vibration amplitudes are concentrated at the wingtips and near the engine. The proposed system offers an accessible and flexible alternative to commercial equipment, integrating acquisition, processing, and real-time visualization. Moreover, its implementation facilitates the early detection of structural anomalies and improves the reliability and safety of UAVs.

This article focuses on the study of the state of the art of theoretical and experimental investigations that carried out vibration analysis in an unmanned aerial vehicle (UAV). According to the review of literature, modal analysis is fundamental to determine the dynamic behaviour of the structure since it studies the nature of the vibrations and the behaviour of the UAV structure under different excitations. One unwanted vibration is flutter, which is a phenomenon that causes structural failure, performance degradation and in the worst case, partial or complete loss of the aircraft structure. The fundamental tool for the analysis of vibrations including flutter is the Fast Fourier Transform. As a result of the analysis of the studies reported in this work, some important points to be considered when implementing modal analysis in UAVs are listed.