Psychoacoustic analysis of contra-rotating propeller noise for unmanned aerial vehicles
Psychoacoustic analysis of contra-rotating propeller noise for unmanned aerial vehicles
Unmanned aerial vehicle (UAV) technologies are rapidly advancing due to the unlimited number of applications from parcel delivery to people transportation. As the UAV market expands, community noise impact will become a significant problem for public acceptance. Compact drone architectures based on contra-rotating propellers bring significant benefits in terms of aerodynamic performance and redundancy to ensure vehicle control in case of component failure. However, contra-rotating propellers are severely noisy if not designed appropriately. In the framework of a perception-influenced design approach, this paper investigates the optimal rotor spacing distance configuration to minimise noise annoyance. On the basis of a series of psychoacoustic metrics (i.e., loudness, fluctuation strength, roughness, sharpness, and tonality) and psychoacoustic annoyance (PA) models, the optimal rotor axial separation
distance (expressed as a function of propeller blade diameter) is at a range from 0.2 to 0.4. This paper also discusses the performance of currently available psychoacoustic models to predict propeller noise annoyance and defines further
work to develop a PA model optimised for rotating systems.
835-846
Torija, Antonio J.
897fc235-0fc5-44e7-9b0d-a78c4c4e36f7
Paruchuri, Chaitanya
5c1def64-6347-4be3-ac2d-b9f6a314b81d
Li, Zhengguang
4efe8369-23ab-4933-8c0c-0f6bdea53c05
3 February 2021
Torija, Antonio J.
897fc235-0fc5-44e7-9b0d-a78c4c4e36f7
Paruchuri, Chaitanya
5c1def64-6347-4be3-ac2d-b9f6a314b81d
Li, Zhengguang
4efe8369-23ab-4933-8c0c-0f6bdea53c05
Torija, Antonio J., Paruchuri, Chaitanya and Li, Zhengguang
(2021)
Psychoacoustic analysis of contra-rotating propeller noise for unmanned aerial vehicles.
The Journal of The Acoustical Society of America, 149 (2), .
(doi:10.1121/10.0003432).
Abstract
Unmanned aerial vehicle (UAV) technologies are rapidly advancing due to the unlimited number of applications from parcel delivery to people transportation. As the UAV market expands, community noise impact will become a significant problem for public acceptance. Compact drone architectures based on contra-rotating propellers bring significant benefits in terms of aerodynamic performance and redundancy to ensure vehicle control in case of component failure. However, contra-rotating propellers are severely noisy if not designed appropriately. In the framework of a perception-influenced design approach, this paper investigates the optimal rotor spacing distance configuration to minimise noise annoyance. On the basis of a series of psychoacoustic metrics (i.e., loudness, fluctuation strength, roughness, sharpness, and tonality) and psychoacoustic annoyance (PA) models, the optimal rotor axial separation
distance (expressed as a function of propeller blade diameter) is at a range from 0.2 to 0.4. This paper also discusses the performance of currently available psychoacoustic models to predict propeller noise annoyance and defines further
work to develop a PA model optimised for rotating systems.
Text
Manuscript_JASA
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More information
Accepted/In Press date: 8 January 2021
Published date: 3 February 2021
Additional Information:
Funding Information:
P.C. would like to acknowledge the financial support of the Royal Academy of Engineering, United Kingdom (RF/ 201819/18/194). The authors would also like to thank Dr. Mantas Brazinskas and Dr. Stephen Prior for their efforts in building this rig at the University of Southampton. Z.L. would like to thank the funding from the Natural Science Foundation of Zhejiang University of Science and Technology (No. 2019QN15).
Publisher Copyright:
© 2021 Acoustical Society of America.
Identifiers
Local EPrints ID: 448468
URI: http://eprints.soton.ac.uk/id/eprint/448468
ISSN: 0001-4966
PURE UUID: 71e437d9-ff8c-475c-b4b9-7144ad51c52b
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Date deposited: 22 Apr 2021 16:47
Last modified: 17 Mar 2024 06:28
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Author:
Antonio J. Torija
Author:
Zhengguang Li
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