Abstract: The airflow vector information is crucial for ensuring flight safety and flow field identification for the increasingly miniaturized drones. However, the measurement of the airflow velocity and direction on small-sized and compatible sensors is still challenging. Natural creatures, such as scorpions, use the trichobothria organ to resolve airflow vectors in a complicated airflow field. Inspired by this sensing capability, we investigate the elliptical-top and cylindrical-root structure of the trichobothria hair shaft. The elliptical top enlarges the deflection difference of the hair shaft between the airflow from sensitive and insensitive directions, which makes the hair shaft an airflow-vector sensor. To replicate this capability, a Bioinspired Elliptical-top and Cylindrical-root Hair sensor (BECH) is designed. The sensor exhibits sensitivities of 16.46 and 9 mV/m/s for the sensitive and insensitive directions, respectively, and detects the airflow velocity and direction with the resolution of 0.064 m/s and 5.08°. To accomplish the recognition of airflow vector, a BECH array was constructed. Based on a Back Propagation Neural Network (BP-NN), the airflow vector is accurately detected with Root Mean Squared Error (RMSE) of 0.00186 and 3.149 for the velocity and direction, respectively. The proposed BECH, inspired by scorpions, provides a new concept for the design of hair-like sensors aiming to decouple airflow vectors.

Key words: Airflow sensor')">Airflow sensor, Bioinspired sensor, Neural network, Airflow vector detection