Vibration Analysis for Anomaly Detection in Unmanned Aircraft

Unmanned aircraft systems are increasingly operating in sensitive airspace which involves risks about the implications of drone activity. As a result, managing safer operations will be crucial to success for the operators. Vibration analysis can provide a detailed examination of drone health status by examining signal levels and frequencies. Thus, this paper investigates how vibration measurements from drone flights can be analysed to infer the condition of the mechanical integrity of the drone. The method should ascertain whether a vibration analysis algorithm can detect major fault progress in drone flights. In order to track and monitor the anomalies on the drone, the research proposes the periodogram method on the vibration data from on-board vibration sensors. The method was tested with an unmanned aircraft with and without full payload, and the results provide support for the proposed algorithm, with the ability to determine anomaly from an unsteady flight but those results being preliminary to further research. This suggests that further drone safety research can use the same signal processing method regarding vibration related anomalies.