In-Situ Health Monitoring of UAV Composite Propulsion Propeller Blades Based On a Flexible Sensing System

For in-situ health monitoring for Unmanned Aerial Vehicle (UAV) composite propulsion propeller blades, MEMS accelerometers are embedded inside the blades, and the vibration signals are acquired in real time using a flexible sensing system. Firstly, the validity of the signals acquired by MEMS accelerometers are verified by a shaker. Secondly, the comparison of the embedded-mounted sensor with surface-mounted sensor is performed. Moreover, in order to signal reduction and feature extraction for blade vibration, Teager energy operator (TEO) is applied to demodulate and enhance the pulse compositions, and singular value decomposition (SVD) is used to eliminate the random environmental noise. The experimental results show that the signals acquired by MEMS accelerometers and flexible sensing system can characterize the vibration of propeller blades. The combination of TEO and SVD effectively demodulates and highlights the characteristic frequencies while eliminating the noise.