Print Email Facebook Twitter Microphones as Airspeed Sensors for Unmanned Aerial Vehicles Title Microphones as Airspeed Sensors for Unmanned Aerial Vehicles Author Makaveev, M.K. (Student TU Delft) Snellen, M. (TU Delft Control & Operations; TU Delft Aircraft Noise and Climate Effects) Smeur, E.J.J. (TU Delft Control & Simulation) Department Control & Operations Date 2023 Abstract This paper puts forward a novel design for an airspeed instrument aimed at small fixed-wing tail-sitter unmanned aerial vehicles. The working principle is to relate the power spectra of the wall-pressure fluctuations beneath the turbulent boundary layer present over the vehicle’s body in flight to its airspeed. The instrument consists of two microphones; one flush-mounted on the vehicle’s nose cone, which captures the pseudo-sound caused by the turbulent boundary layer, and a micro-controller that processes the signals and computes the airspeed. A feed-forward single-layer neural network is used to predict the airspeed based on the power spectra of the microphones’ signals. The neural network is trained using data obtained from wind tunnel and flight experiments. Several neural networks were trained and validated using only flight data, with the best one achieving a mean approximation error of 0.043 m/s and having a standard deviation of 1.039 m/s. The angle of attack has a significant impact on the measurement, but if the angle of attack is known, the airspeed could still be successfully predicted for a wide range of angles of attack. Subject tail-sitterairspeedhydrodynamic pressure fluctuationspseudo-soundturbulent boundary layermicrophonespower spectral densityfeed-forward neural networks To reference this document use: http://resolver.tudelft.nl/uuid:626768d7-b4ef-47a9-bb98-10e449320f2e DOI https://doi.org/10.3390/s23052463 ISSN 1424-8220 Source Sensors, 23 (5) Part of collection Institutional Repository Document type journal article Rights © 2023 M.K. Makaveev, M. Snellen, E.J.J. Smeur Files PDF sensors_23_02463.pdf 5.66 MB Close viewer /islandora/object/uuid:626768d7-b4ef-47a9-bb98-10e449320f2e/datastream/OBJ/view