Propeller Noise in Confined Anechoic and Open Environments

Whelchel, Jeremiah; Alexander, William N.; Intaratep, Nanyaporn

doi:10.2514/6.2020-1252

Cited by 16 publications

(7 citation statements)

References 3 publications

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“…Gojon et al (Gojon et al, 2021) also discussed the balance between tonal and broadband noise contributions as a function of blade number, i.e., an increase in blade number led to a decrease in BPF amplitude but an increase in broadband noise. Zawodny and Boyd (Zawodny and Boyd, 2019) and Whelchel et al (Whelchel et al, 2020) studied the rotor-airframe interaction for a variety of simplified configurations. More complex configurations like multi-rotors have been investigated by Intaratep et al (Intaratep et al, 2016) and Tinney and Sirohi (Tinney and Sirohi, 2018).…”

Section: Introductionmentioning

confidence: 99%

Psychoacoustic modelling of rotor noise

Torija

Paruchuri

2022

The Journal of the Acoustical Society of America

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The aviation sector is rapidly evolving with more electric propulsion systems and a variety of new technologies of vertical take-off and landing manned and unmanned aerial vehicles. Community noise impact is one of the main barriers for the wider adoption of these new vehicles. Within the framework of a perception-driven engineering approach, this paper investigates the relationship between sound quality and first order physical parameters in rotor systems to aid design. Three case studies are considered: (i) contra-rotating versus single rotor systems, (ii) varying blade diameter and thrust in both contra-rotating and single rotor systems, and (iii) varying rotor–rotor axial spacing in contra-rotating systems. The outcomes of a listening experiment, where participants assessed a series of sound stimuli with varying design parameters, allow a better understanding of the annoyance induced by rotor noise. Further to this, a psychoacoustic annoyance model optimised for rotor noise has been formulated. The model includes a novel psychoacoustic function to account for the perceptual effect of impulsiveness. The significance of the proposed model lies in the quantification of the effects of psychoacoustic factors, such as loudness as the dominant factor, and also tonality, high frequency content, temporal fluctuations, and impulsiveness on rotor noise annoyance.

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Section: Introductionmentioning

confidence: 99%

Psychoacoustic modelling of rotor noise

Torija

Paruchuri

2022

The Journal of the Acoustical Society of America

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“…The noise emission of drones and isolated drone propellers have been extensively studied [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. Hui et al [ 3 ] outlined the main sound generation mechanisms in drones, highlighting the contributions of rotor noise and electric motors.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Metrics for Assessing Human Response to Drone Noise

Torija

Nicholls

2022

IJERPH

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Novel electric air transportation is emerging as an industry that could help to improve the lives of people living in both metropolitan and rural areas through integration into infrastructure and services. However, as this new resource of accessibility increases in momentum, the need to investigate any potential adverse health impacts on the public becomes paramount. This paper details research investigating the effectiveness of available noise metrics and sound quality metrics (SQMs) for assessing perception of drone noise. A subjective experiment was undertaken to gather data on human response to a comprehensive set of drone sounds and to investigate the relationship between perceived annoyance, perceived loudness and perceived pitch and key psychoacoustic factors. Based on statistical analyses, subjective models were obtained for perceived annoyance, loudness and pitch of drone noise. These models provide understanding on key psychoacoustic features to consider in decision making in order to mitigate the impact of drone noise. For the drone sounds tested in this paper, the main contributors to perceived annoyance are perceived noise level (PNL) and sharpness; for perceived loudness are PNL and fluctuation strength; and for perceived pitch are sharpness, roughness and Aures tonality. Responses for the drone sounds tested were found to be highly sensitive to the distance between drone and receiver, measured in terms of height above ground level (HAGL). All these findings could inform the optimisation of drone operating conditions in order to mitigate community noise.

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“…These generate tonal noise which is usually significant at the first two or three harmonics of the blade passing frequency and which radiates strongly close to the plane of the propeller [15,17]; A significant number of papers have appeared in the recent literature investigating the noise produced by UAVs. Some report measurements of noise from UAVs in flight (e.g., [7][8][9][10][11]), from full or partial UAVs statically mounted in an anechoic chamber (e.g., [12][13][14]), and also from isolated UAV propellers statically mounted in an anechoic chamber with or without a flight stream (e.g., [15][16][17][18][19]). These and other investigations have identified that the noise produced by UAVs is mostly caused by the rotors and the electric motors which power them.…”

mentioning

confidence: 99%

“…Figure11. Correlation matrix between annoyance ratings and objective measurements for hover noise events.…”

mentioning

confidence: 99%

Quantification of the Psychoacoustic Effect of Noise from Small Unmanned Aerial Vehicles

Hui

Kingan

Hioka

et al. 2021

IJERPH

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This paper presents the results of a study evaluating the human perception of the noise produced by four different small quadcopter unmanned aerial vehicles (UAVs). This study utilised measurements and recordings of the noise produced by the quadcopter UAVs in hover and in constant-speed flight at a fixed altitude. Measurements made using a ½″ microphone were used to calculate a range of different noise metrics for each noise event. Noise recordings were also made using a spherical microphone array (an Eigenmike system). The recordings were reproduced using a 3D sound reproduction system installed in a large anechoic chamber located at The University of Auckland. Thirty-seven participants were subjected to the recordings and asked to rate their levels of annoyance in response to the noise, and asked to perform a simple cognitive task in order to assess the level of distraction caused by the noise. This study discusses the noise levels measured during the test and how the various noise metrics relate to the annoyance ratings. It was found that annoyance strongly correlates with the sound pressure level and loudness metrics, and that there is a very strong correlation between the annoyance caused by a UAV in hover and in flyby at the same height. While some significant differences between the distraction caused by the UAV noise for different cases were observed in the cognitive distraction test, the results were inconclusive. This was likely due to a ceiling effect observed in the participants’ test scores.

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Propeller Noise in Confined Anechoic and Open Environments

Cited by 16 publications

References 3 publications

Psychoacoustic modelling of rotor noise

Psychoacoustic modelling of rotor noise

Investigation of Metrics for Assessing Human Response to Drone Noise

Quantification of the Psychoacoustic Effect of Noise from Small Unmanned Aerial Vehicles

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