Professor of Mechanical Engineering and Smart Structures, School of Computing Engineering and Mathematics, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—UAVs are now applied to various fields, from military missions to civilian applications. A malfunction in the drone’s thrust system during flights can result in collisions and damages of property or human injury. To prevent this, the tolerant control of the multicopter has been studied to stabilize attitude, but it tends to focus on short-sighted management. In this paper, we propose an overall fault diagnostic technique for the UAV motor itself. To do this, we derive a model for the UAV motor in the normal steady-state using a nonlinear equation, which is then experimentally verified with 99% accuracy. We consider bearing friction increase, phase open, propeller broken, transistor open, and back EMF signal errors for malfunction of UAV motor, and we suggest a simple fault diagnosis algorithm by an analysis of the fault characteristics. We show the effectiveness of our diagnostic technique by the experimental results of the testbed and flight model.
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