scholarly journals Wing-Beat Frequency and Its Acoustics in Birds and Bats

2020 ◽  
Vol 60 (5) ◽  
pp. 1080-1090 ◽  
Author(s):  
Arjan Boonman ◽  
Yossi Yovel ◽  
Ofri Eitan
Keyword(s):  
Sound Pressure ◽  
Acoustic Noise ◽  
Beat Frequency ◽  
Average Frequency ◽  
Positive Pressure ◽  
Wind Noise ◽  
Wing Movement ◽  
Downward Motion ◽  
Motion Paths ◽  
Animal Flight

Synopsis Animal flight noise can serve as an inspiration to engineering solutions to wind-noise problems in planes or wind turbines. Here we investigate the acoustics of wingbeats in birds and bats by co-registering wing-movement in natural flight with acoustic noise. To understand the relationships between wing movement and acoustics, we conducted additional acoustic measurements of single moving wings and other moving surfaces with accurately tracked motion paths. We found a correlation between wing-surface area and the sound pressure level of wingbeats; with bats tending to produce lower levels than birds. Measuring moving wings in isolation showed that a downstroke toward a microphone causes negative sound pressure that flips back into positive pressure at the reversal to the upstroke. The flip back to positive pressure is unrelated to the action of the upstroke, but occurs when the downward motion is halted. If the microphone is positioned above the downward wingbeat, then sound pressure instead quickly rises during the downward motion of the wing. The phase pattern of the impulse created by the wingbeat varies systematically with recording-angle. The curvature of the wing appears to be a determinant of the average frequency of the acoustic impulse. Our findings can be used to predict the acoustics of smaller flying animals where repetition pitch of similar underlying impulses, repeated at much higher wingbeat-rates become dominant.

Variation in vibro-acoustic noise due to the defects in an automotive drum brake

2021 ◽  
Vol 263 (4) ◽  
pp. 2646-2653
Author(s):  
Ananthapadmanabhan Ramesh ◽  
Sundar Sriram
Keyword(s):  
Analytical Model ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Transfer Functions ◽  
Acoustic Noise ◽  
Pressure Level ◽  
Acoustic Model ◽  
Drum Brake ◽  
Non Linear ◽  
Sound Pressure Levels

Drum brakes are significant contributors to noise and vibration in automobiles causing discomfort to the passengers. The vibration and hence the resulting noise increase due to various inherent defects in the drum brake, such as asymmetry. This work aims to quantify the variation in the vibro-acoustic noise due to several common defects in the drum brake using an integrated non-linear vibration analytical model and a numerical acoustic model. The sources of vibro-acoustic noise sources such as contact and reaction forces are predicted using a four-degree-of-freedom non-linear contact mechanics based analytical model. A finite element based acoustic model of the drum brake is utilized to predict the force to the sound pressure transfer function in the drum brake. Product of the transfer functions and the forces gives the corresponding sound pressure level from which the overall sound pressure levels are estimated. The variation in the overall sound pressure levels due to different drum brake defects is evaluated by introducing defects to the analytical model. The results show that the overall sound pressure level is a strong function of the defects. It is envisioned that the current work will help in the development of effective health monitoring systems.

Far-Field Noise Control in Supersonic Jets From Conical and Contoured Nozzles

2011 ◽  
Vol 133 (8) ◽  
Author(s):  
Jin-Hwa Kim ◽  
Martin Kearney-Fischer ◽  
Mo Samimy ◽  
Sivaram Gogineni
Keyword(s):  
Sound Pressure ◽  
Acoustic Noise ◽  
Microphone Array ◽  
Plasma Actuators ◽  
Far Field ◽  
Free Jet ◽  
Naturally Occurring ◽  
Mixing Noise ◽  
Field Noise ◽  
Jet Axis

Plasma actuators are used to control far-field noise in Mach 1.65 jets from contoured and conical supersonic axisymmetric nozzles (henceforth, contoured and conical jets, respectively). The contoured nozzle is designed using the method of characteristics for a shock-free jet. The conical nozzle has converging and diverging conical sections with a sharp throat. Eight plasma actuators, distributed uniformly around the nozzle exit, are used and the jet is forced with azimuthal modes (m) 0–3 and ±4 and forcing Strouhal numbers ranging from 0.09 to 4.0. The far-field acoustic noise is measured by a linear microphone array covering polar angles from 25 deg to 80 deg relative to the jet axis. In both jets, the lower forcing azimuthal modes (m=0 and 1) are less effective than the higher modes (m=2, 3, and ±4), which have similar levels of overall sound pressure level (OASPL) reduction. At shallow angles relative to the jet axis, the reduction in OASPL is about 1.6–1.8 dB at low forcing Strouhal numbers in both jets at the most effective forcing mode of m=3. However, the OASPL in the sideline direction is only slightly increased (about 1 dB) for both the contoured and conical jets at m=3. The reduction at shallow polar angles is related to the decrease in the peak mixing noise level in both jets. The range of forcing Strouhal numbers providing significant noise reduction and the range of polar angles over which the noise is reduced are both much larger in the conical jet compared with the contoured jet. The screech tones are also reduced or suppressed – most likely due to weakening of naturally occurring structures by forcing.

scholarly journals Identification and analysis of noise sources in the Noor-Abad gas compressor station, Iran

2015 ◽  
Vol 4 (1) ◽  
pp. 196
Author(s):  
Nader Mohammadi ◽  
Kami Mohammadi
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Acoustic Noise ◽  
Noise Pollution ◽  
Residential Area ◽  
Pressure Level ◽  
Compressor Station ◽  
Noise Condition ◽  
Noise Sources ◽  
Noise Map

The objective of this study is to identify the sources of acoustic noise (noise pollution) in the Noor-Abad gas compressor station and then to prioritize the station equipment based on noise pollution. First, the key locations inside the station as well as in the surrounding residential area, aka the study area, are determined for the measurement of sound pressure level. Then, the sound pressure level is measured at those points, and the related noise map is produced. Based on the noise map, the noise condition in the study area is evaluated by comparing the measured acoustic parameters with allowable standard values. Dangerous regions and critical points are thus identified. The major noise sources consist of main blowdown, units’ blowdowns, scrubbers, and turbo-compressors. The sound pressure level of main blowdown is measured at two intervals from its position: 80 m inside the station and 600 m outside the station (at the edge of the surrounding residential area). Also, the sound pressure level for a unit blowdown and a scrubber is measured at respectively 25 m and 40 m from their positions. Finally, the station equipment is prioritized based on noise pollution. The analysis of measurement results showed that the main noise sources are, respectively, the station main blowdown, units’ scrubbers, units’ blowdowns, turbo-compressors, and gas pipelines.

scholarly journals Synthesis of algorithm of unmanned aerial vehicle detection by acoustic noise

Doklady BGUIR ◽  
2021 ◽  
Vol 19 (2) ◽  
pp. 65-73
Author(s):  
A. D. Puzanau ◽  
D. S. Nefedov
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Acoustic Noise ◽  
Signal To Noise Ratio ◽  
Weather Conditions ◽  
Wind Noise ◽  
Detection Range ◽  
Detection Systems ◽  
A Value ◽  
Coherent Accumulation ◽  
Aerial Vehicle

 The algorithm of detection of acoustic noise provided by an unmanned aerial vehicle (UAV) in the noise background due to wind is synthesized in the article. Creation of the algorithm has been carried out using the Neyman – Pearson lemma. The algorithm assumes a combination of the stages of wind noise coherent compensation and coherent accumulation of UAV’s acoustic noise sound pressure impulses. The coherent accumulation time matches doubled time of fluctuation correlation resulted by experimental research of acoustic noise of different types of  UAVs. Efficiency of the developed algorithm of UAV detection depends on flight velocity, foreshortening, amount of blades and rotor turnovers of UAV as well as weather conditions. For the probability of a false alarm value of 10–4, the probability of correct UAV detection value of 0.9 is provided wherein signal-to-noise ratio has a value of 8 dB. These indicators correspond the detection range of 200 to 300 meters. The obtained results allow discussions about perspective of acoustic UAVs detection systems adaptation. 

MRI acoustic noise: Sound pressure and frequency analysis

1997 ◽  
Vol 7 (3) ◽  
pp. 606-611 ◽  
Author(s):  
S. Allen Counter ◽  
Ake Olofsson ◽  
H. F. Grahn ◽  
Erik Borg
Keyword(s):  
Frequency Analysis ◽  
Sound Pressure ◽  
Acoustic Noise

MEASUREMENT AND SIMULATION FOR WIND NOISES IN THE OCEAN ENVIRONMENTS WITH NONLINEAR INTERNAL WAVES

2008 ◽  
Vol 16 (02) ◽  
pp. 163-176 ◽  
Author(s):  
HSIANG-CHIH CHAN ◽  
RUEY-CHANG WEI ◽  
CHI-FANG CHEN
Keyword(s):  
Internal Waves ◽  
Sound Speed ◽  
Environmental Changes ◽  
Acoustic Noise ◽  
Propagation Model ◽  
Wind Noise ◽  
Nonlinear Internal Waves ◽  
Line Array ◽  
Noise Data ◽  
Water Temperature Data

This study obtains wind noise variations by experimental data and simulated results to describe meteorological and oceanic effects. The ambient noise data were measured by a vertical line array in the 2001 ASIAEX South China Sea experiment. An acoustic propagation model is used in noise modeling for calculating the sound pressure of noises at receiving sites, including the effects of ocean environmental changes, bottom interactions, and noise fluctuations at different depths. Both range-independent and range-dependent sound speed profiles are generated with in-situ water temperature data. Results show fluctuating noise levels with variations in ocean environments. But the fluctuations are small such that only weak correlation exists in the acoustic noise data and ocean data. Results also indicate that using range-independent sound speed profiles can simulate noise field in range-dependent ocean environments with nonlinear internal waves for shallow regions with flat bottoms.

Testing Propeller Tip Modifications to Reduce Acoustic Noise Generation on a Quadcopter Propeller

2019 ◽  
Vol 141 (12) ◽  
Author(s):  
Kenneth W. Van Treuren ◽  
Charles F. Wisniewski
Keyword(s):  
Sound Pressure ◽  
Acoustic Noise ◽  
Near Field ◽  
Tip Vortex ◽  
Noise Generation ◽  
Radial Location ◽  
Power Increase ◽  
Vertical Lift ◽  
Near Field Sound ◽  
Field Sound

Abstract If vertical lift vehicles are to operate near population centers, they must be both quiet and efficient. The goal of this research is to develop a propeller that is more efficient and generates less noise than a stock DJI Phantom 2 quadcopter propeller. Reducing the generated tip vortex was the main objective. After studying the literature, seven promising tip treatments were selected and applied to a stock DJI Phantom 2 propeller to reduce the tip vortex. Several different configurations were tested for each tip treatment to determine the rpm and required power to hold 0.7 lbf thrust, the static hover condition. For each test, operating at the hover condition, a radial traverse 1 in. behind the propeller permitted the measurement of the near field sound pressure level (SPL) to find the maximum SPL and its radial location. Several configurations tested resulted in 8–10 dBA reductions in SPL when compared to the stock propeller; however, these configurations also resulted in an unacceptable increase in the power required to achieve the desired thrust. The most promising tip treatment tested was the trailing edge (TE) notch at a radial location of 0.95 r/R with a double slot width and a double depth (DSDD). The DSDD configuration as tested reduced the SPL 7.2 dBA with an increase in power required of only 3.96% over the stock propeller. This tradeoff, while not the largest reduction in noise generation measured, had an acceptable power increase for the decrease in SPL achieved.

Far-Field Noise Control in Supersonic Jets From Conical and Contoured Nozzles

2010 ◽  
Author(s):  
Jin-Hwa Kim ◽  
Martin Kearney-Fischer ◽  
Mo Samimy ◽  
Sivaram Gogineni
Keyword(s):  
Sound Pressure ◽  
Acoustic Noise ◽  
Microphone Array ◽  
Plasma Actuators ◽  
Far Field ◽  
Free Jet ◽  
Naturally Occurring ◽  
Mixing Noise ◽  
Field Noise ◽  
Jet Axis

Plasma actuators are used to control far-field noise in Mach 1.65 jets from contoured and conical supersonic axisymmetric nozzles (henceforth contoured and conical jets, respectively). The contoured nozzle is designed using the method of characteristics for shock-free jet. The conical nozzle has converging and diverging conical sections with a sharp throat. Eight plasma actuators, distributed uniformly around the nozzle exit, are used and the jet is forced with azimuthal modes (m) 0–3, and ±4 and forcing Strouhal numbers ranging from 0.09 to 4.0. The far-field acoustic noise is measured by a linear microphone array covering polar angles from 25 to 80° relative to the jet axis. In both jets, the lower forcing azimuthal modes (m = 0 and 1) are less effective than the higher modes (m = 2, 3, and ±4), which have similar levels of overall sound pressure level (OASPL) reduction. At shallow angles relative to the jet axis, the reduction in OASPL is about 1.6–1.8 dB at low forcing Strouhal numbers in both jets at the most effective forcing mode of m = 3. However, the OASPL in the sideline direction is only slightly increased (about 1 dB) for both the contoured and conical jets at m = 3. The reduction at shallow polar angles is related to the decrease in the peak mixing noise level in both jets. The range of forcing Strouhal numbers providing significant noise reduction and the range of polar angles over which the noise is reduced, are both much larger in the conical jet compared to the contoured jet. The screech tones are also reduced or suppressed most likely due to weakening of naturally occurring structures by forcing.

scholarly journals Humming hummingbirds, insect flight tones and a model of animal flight sound

2020 ◽  
Vol 223 (19) ◽  
pp. jeb214965
Author(s):  
Christopher J. Clark ◽  
Emily A. Mistick
Keyword(s):  
Sound Pressure ◽  
Insect Flight ◽  
Aerodynamic Force ◽  
Sound Field ◽  
Far Field ◽  
Aerodynamic Forces ◽  
Wingbeat Frequency ◽  
Predator Prey ◽  
Aerodynamic Pressure ◽  
Animal Flight

ABSTRACTWhy do hummingbirds hum and insects whine when their wings flap in flight? Gutin proposed that a spinning propeller produces tonal sound because the location of the center of aerodynamic pressure on each blade oscillates relative to an external receiver. Animal wings also move, and in addition, aerodynamic force produced by animal wings fluctuates in magnitude and direction over the course of the wingbeat. Here, we modeled animal wing tone as the equal, opposite reaction to aerodynamic forces on the wing, using Lowson's equation for the sound field produced by a moving point force. Two assumptions of Lowson's equation were met: animal flight is low (<0.3) Mach and animals from albatrosses to mosquitoes are acoustically compact, meaning they have a small spatial extent relative to the wavelength of their wingbeat frequency. This model predicted the acoustic waveform of a hovering Costa's hummingbird (Calypte costae), which varies in the x, y and z directions around the animal. We modeled the wing forces of a hovering animal as a sinusoid with an amplitude equal to body weight. This model predicted wing sound pressure levels below a hovering hummingbird and mosquito to within 2 dB; and that far-field mosquito wing tone attenuates to 20 dB within about 0.2 m of the animal, while hummingbird humming attenuates to 20 dB at about 10 m. Wing tone plays a role in communication of certain insects, such as mosquitoes, and influences predator–prey interactions, because it potentially reveals the predator's presence to its intended prey.

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