Drone Noise Reduction Using Serration–Finlet Blade Design and Its Psychoacoustic and Social Impacts

Yingyin Shen (), Yuanqing Bai, Xiao Liu and Bin Zang
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Yingyin Shen: School of Social Sciences, Soochow University, Suzhou 215006, China
Yuanqing Bai: School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
Xiao Liu: School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol BS8 1QU, UK
Bin Zang: School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol BS8 1QU, UK

Sustainability, 2025, vol. 17, issue 8, 1-19

Abstract: Unmanned aerial vehicles, particularly drones, have been increasingly deployed for different tasks in the community. They have become an important part of the economic and social benefits that society is exploiting from modern technology development. However, efforts are still required to further develop technologies which can mitigate the negative impacts. Among them, drone noise is considered a major health concern for the community. The present study undertakes an experimental investigation of the effectiveness of blade modifications on drone noise in an aeroacoustic wind tunnel facility. A quadcopter drone is programmed to operate in both hover and forward flights. Three modified blade configurations, including trailing-edge serrations combined serration–finlets, and an unmodified (baseline) blade, are manufactured. The far-field noise signals are recorded by two polar microphone arrays to quantify both the magnitude and directivity. The results show that all modified blades are able to reduce the drone noise at mid-to-high frequencies in both hover and forward flights, and this leads to a noticeable reduction in the overall sound pressure level. More importantly, the combined serration–finlet configuration outperforms all the other blades. Psychoacoustic analysis is also performed using the far-field acoustic time series. Interestingly, only the serration–finlet combination demonstrates a consistent reduction in the psychoacoustic annoyance levels, suggesting that it is important to use metrics from both acoustic and psychoacoustic analysis when developing noise mitigation strategies in the socio-economic context.

Keywords: drone noise; novel blade design; noise impact reduction; psychoacoustics of drones (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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