Structural Health Monitoring of Multi-Rotor Micro Aerial Vehicles

Abstract

Structural Health Monitoring (SHM) is a key troubleshooting methodology for assessing the working condition and health of (manned or unmanned) aerial vehicles; however, its understanding with respect to the multi-rotor class of Micro Aerial Vehicles (MAV) is limited. The portentous structural failure sources, in this case, are the two moving components: motors and propellers. In this paper, we undertake a detailed exercise of characterizing the common and frequent faults of these units using multi-modal sensing of vibration, acoustic noise, input power, and thrust profiles; and then use relevant features to perform a two-level diagnosis. Through our empirical fault studies on our custom designed test rig, we propose a set of befitting features in each sensory domain; which result in high fault detection and classification accuracy that exceeds 90%.