Bio-inspired, intelligent flexible sensing skin for multifunctional flying perception.

Developing multifunctional flying perceptibility, by mimicking the biological system, is meaningful for aircrafts to adapt to the complicated and ambiguous flow environment. In this work, we show that the comprehensive capabilities (skin, synapse, immune system, and brain) of flying creatures can serve as bio-inspirations to develop an intelligent flexible sensing (iFlexSense) skin with similar components, i.e., skin-like mechanosensing, neuron-like data transmission, immune system-like impact monitoring and brain-like artificial intelligence. The iFlexSence skin brings substantial improvements to the aircrafts by the multifunctionalities including airflow perception, state awareness and self-diagnosis of complex surfaces, validated by the wind tunnel tests mounted on a NACA 0012 airfoil, in which it accurately measures the surface pressure, temperature, wall shear stress and flutter, locates the sudden impacts and correctly predicts the occurrence of separation and stall. It shows great potential for future wind tunnel tests and to extend the capabilities of unmanned air vehicles and underwater vehicles. Bio-inspired the unprecedented flying perceptibility of flying creatures, a large-area intelligent flexible sensing skin is proposed for full-covered multifunctional external airflow sensing and internal structural health monitoring of aircrafts. The multi-sensor data fusion method can help accurately and reliably evaluate or predict flow characteristics and health managements, such as airflow separation, airplane flutter, stall warning and impact locating. [Display omitted] • A bio-inspired electronic skin for aircrafts demonstrates multifunctional airflow sensing and structural health monitoring. • The multiple sensors comprehensively reveal the flow characteristics, such as flow separation, airplane flutter and stall. • The health monitoring system identifies and localizes the sudden impacts via machine-learning based passive method. • The multi-data fusion can help provide accurate and reliable information for flying perception. [ABSTRACT FROM AUTHOR]