Vibration Analysis for Anomaly Detection in Unmanned Aircraft

Abstract

Vibration analysis is a vital measurement tool to provide detailed examination of drone health status by examining signal levels and frequencies. As drones are progressively operating in susceptible airspace where their being might cause harm, signal processing of in-flight data is becoming a necessity to reduce drone risks in sensitive conditions. On that account, this paper investigates how vibration measurements from different flights can be analysed to infer the condition of elements inside the drone. The results should assist safety operators to ascertain whether vibration anomalies can be an indicator of diagnostic and troubleshooting tools of major fault progress in drone flights. In order to track and monitorize the anomalies on the flying drone, this research proposes a vibration spectrum analysis on the inputs from on-board vibration monitoring sensors. The reason for using this analysis is that it can conduct the anomaly detection by providing critical frequency information pinpointing the faulty conditions on the drone platform. The results provides support for the proposed framework, with the ability to determine increasing defect from an unsteady flight with high payload but those results being preliminary to further research. This suggests that further drone safety research can use the same signal processing themes regarding vibration related anomalies when operating in sensitive flight zones.