Dynamics Model of a Multi-Rotor UAV Propeller and Its Fault Detection

The propeller state of unmanned aerial vehicles (UAV) is difficult to detect in real time due to trouble with laying out the sensor and multiple signal sources. To solve this problem, a fault detection method for multi-rotor UAV propellers was proposed based on a signal analysis of the built-in inertial measurement unit (IMU). Firstly, the multi-source coupled signals of the UAV flight were obtained through the ground station. Then, the picked-up signals were optimally separated according to the multi-rotor UAV propeller fault dynamics model, and signals rich in fault information were obtained. Finally, the separated signals were calculated using the symmetrized dot pattern (SDP), and then the similarity index was used to quantify the distribution of the signal in the feature plot to realize propeller fault detection. The OTSU algorithm was used to quantify the detection results, yielding a similarity of 76.2% in the z-axis direction, which is better than the values in the other two directions. The simulation and experimental analysis of the propeller failure dynamics model showed that the proposed method can effectively identify the propeller faults of multi-rotor UAVs.