Unmanned Aircraft Systems (UAS) are used for a variety of purposes. Especially the industrial or professional use of UAS will lead to an increasing number of possible applications. The steadily increasing number of drones raises the question of noise impact from these unmanned aircraft. Therefore, the German Environment Agency has started with acoustic investigations of drones. Various small UAS models (i.e. multicopter) were used in a measurements campaign. For example, overflights at different altitudes and speeds were measured. In addition, binaural measurements were performed to provide psychoacoustic findings. In this paper the measurements and results are presented. Overflight levels are compared with psychoa-coustic quantities such as loudness or sharpness. Likewise, conclusions are drawn for the evaluation of drone noise, which can be used for future regulations or standardization. © International Institute of Acoustics and Vibration (IIAV), 2023


    Access

    Download

    Check availability in my library


    Export, share and cite



    Title :

    Noise measurements from drones to estimate future noise exposures


    Contributors:
    Foerster, Jan (author) / Treichel, Julia (author) / De Haag, Maarten Uijt (author) / University, My (host institution)

    Publication date :

    2023


    Size :

    1 Online-Resource (8) pages



    Type of media :

    Miscellaneous


    Type of material :

    Electronic Resource


    Language :

    English


    Keywords :


    Noise prediction of drones in urban environments

    Bian, Haoyu / Fattah, Ryu J. / Sun, Yuhao et al. | AIAA | 2019


    Multi-rotor tonal noise control for drones

    PANTALONE GIULIA / WOODWORTH ADAM / TAYLOR EDWARD et al. | European Patent Office | 2023

    Free access

    Gender differences in noise concerns about civil drones

    End, Albert / Vogelpohl, Verena / Eißfeldt, Hinnerk | TIBKAT | 2021

    Free access

    Noise Reduction in Drones using Silent Electric Ducted Fan

    Kumbhar, Rameshwar / Thombare, Dhawal / Khadake, Atharva et al. | IEEE | 2024