A Charge Supplement Strategy Enhanced Non-contact Triboelectric Sensor for In Situ Blade Lift Monitoring of Unmanned Aerial Vehicles

Real-time monitoring of blade lift is critical for the flight stability and safety of unmanned aerial vehicles (UAVs); however, conventional electronic speed controller estimation methods exhibit limited accuracy, high hardware costs, and susceptibility to signal drift. To address these challenges, this work proposes a self-powered, real-time UAV rotor lift monitoring sensor based on a non-contact triboelectric nanogenerator (BL-TENG). By combining computational fluid dynamics simulations with structural optimization designs, the in situ monitoring of lift force is successfully realized. Furthermore, the introduction of natural rabbit fur as an active charge pump yields a 2.6-fold enhancement in electrical output, while material wear and mechanical drag are minimized through the integration of a non-contact electrode configuration and a soft-contact charge replenishment strategy. Extensive durability testing demonstrates an exceptional voltage retention rate of 98.7% after 10 h of continuous high-speed operation (approximately 1.93 million cycles). Systematic evaluations demonstrate notable lift sensing accuracy, achieving a correlation coefficient exceeding 0.999. In addition, the sensor exhibits strong environmental adaptability, maintaining stable outputs across diverse temperature and humidity conditions, as well as under multisource interferences including spatial tilting, fuselage vibrations, and cross-wind perturbations. Through wireless signal transmission, UAV flight experiments validate the capability for real-time monitoring of aerodynamic lift across dynamic flight phases, such as takeoff and hovering. This work provides a low-cost, highly reliable sensing paradigm for future closed-loop flight control and UAV safety assurance.