Wind-induced Noise Research Articles

Innovative design of façade elements to limit wind-induced noise in buildings

Wind-induced noise is often overlooked in building design. This noise can be generated by wind blowing across façade elements or through the various gaps inside buildings. Noise generated by wind-affected façade elements, particularly at higher wind speeds, has received increasing attention since the 2010s. In this paper a comprehensive literature review is carried out to draw general rules for limiting wind-induced noise in buildings. Next, an innovative design was proposed by Metravib Engineering for the Rabat Ibn Sina hospital designed by AIA Ingénierie. A dynamic analysis of these sunshades was then verified using the finite element method to ensure there was no vibro-acoustic coupling between wind excitation and the sunshade's structural modes. Finally, wind tunnel tests confirmed that the noise induced by these façade elements was under control and did not cause any particular annoyance.

Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network

Passive Acoustic Monitoring (PAM), which involves using autonomous record units for studying wildlife behaviour and distribution, often requires handling big acoustic datasets collected over extended periods. While these data offer invaluable insights about wildlife, their analysis can present challenges in dealing with geophonic sources. A major issue in the process of detection of target sounds is represented by wind-induced noise. This can lead to false positive detections, i.e., energy peaks due to wind gusts misclassified as biological sounds, or false negative, i.e., the wind noise masks the presence of biological sounds. Acoustic data dominated by wind noise makes the analysis of vocal activity unreliable, thus compromising the detection of target sounds and, subsequently, the interpretation of the results. Our work introduces a straightforward approach for detecting recordings affected by windy events using a pre-trained convolutional neural network. This process facilitates identifying wind-compromised data. We consider this dataset pre-processing crucial for ensuring the reliable use of PAM data. We implemented this preprocessing by leveraging YAMNet, a deep learning model for sound classification tasks. We evaluated YAMNet as-is ability to detect wind-induced noise and tested its performance in a Transfer Learning scenario by using our annotated data from the Stony Point Penguin Colony in South Africa. While the classification of YAMNet as-is achieved a precision of 0.71, and recall of 0.66, those metrics strongly improved after the training on our annotated dataset, reaching a precision of 0.91, and recall of 0.92, corresponding to a relative increment of >28 %.Our study demonstrates the promising application of YAMNet in the bioacoustics and ecoacoustics fields, addressing the need for wind-noise-free acoustic data. We released an open-access code that, combined with the efficiency and peak performance of YAMNet, can be used on standard laptops for a broad user base.

Singing buildings: effects and potential causes of wind-induced noise from balcony systems

Modern high-rise residential buildings are wrapped in balcony railings of a countless number of styles, shapes, and materials. This study investigates the effects and potential causes of wind-induced noise and vibration caused by balcony railings; a phenomenon that continues to gain significance in urban environments. This study includes field measurements to quantify the extent and nature of wind-induced noise and vibration from various balcony railing designs exposed to a wide variety of meteorological conditions. A detailed examination of potential causes is also undertaken, considering material properties, structural design, and aerodynamic characteristics. Finite element analysis is employed to model and simulate the dynamic response of several different balcony railings, providing insights into the key factors influencing noise generation. The findings of this study offer practical insights into optimizing balcony railing designs to minimize wind-induced noise.

Measurement and quantification of low frequency noise emissions from utility-scale wind turbines

In wind turbine project permit hearings and other proceedings, concerns are often raised regarding low frequency noise (LFN). As the size of utility-scale wind turbines continues to grow, the concern over LFN may only intensify. This paper describes the measurement and quantification of low frequency noise emissions from utility-scale wind turbines, specifically in the 16, 31.5, and 63 Hertz octave bands. Accurate measurement of wind turbine noise emissions, particularly in the 16 Hertz octave band, is challenging due to interference from wind-induced noise. Topics covered include choice of windscreen, the effectiveness of shutdown tests, data filtering techniques, and the comparison of measured levels at multiple wind turbine sites to levels predicted using manufacturer's data and the ISO 9613-2:1996 method.

Performance comparison of measurement microphones and microbarometers for sound pressure measurements near wind power plants

Reliable assessment of airborne infrasound emitted by natural and technical sources has been gaining importance, while technology is limited and regulations are not sufficient in the infrasound frequency range. This paper provides a comparison of measurement microphones and microbarometers used for infrasound measurements in the field near wind power plants. Simultaneous measurements with both sensor systems were conducted at multiple sites in the vicinity of a wind park. Based on these measurements, it was shown that wind-induced noise is a major concern when measuring infrasound in the field. For this reason, additional experiments were conducted in an aeroacoustic wind tunnel to further investigate the sensitivity to wind of the sensors used. A combination of field measurements and laboratory experiments was applied to determine the influence of wind-induced noise in a real-life situation and multiple strategies are discussed for establishing quality criteria and controlling the influence of wind on such measurements.

Analysis and application of spatio-temporal correlation characteristics of measured ocean ambient noise

Gain in sonar signal processing is closely linked to the spatio-temporal coherence characteristics of the ocean ambient noise field. The gain relies on the spatio-temporal coherence coefficient of the signal and noise, with the aim of maximizing the former and minimizing the latter. Currently, there has been ample research on the spatial characteristics of the noise field, while studies on the temporal coherence characteristics of single-point noise fields are limited. In this paper, a temporal and spatial coherence model of wind-induced noise is established based on the normal mode theory, and the impact of bandwidth and spectral structure on the time coherence coefficient of wind-induced noise is analyzed.To measure the environmental noise in 103 m of shallow water in the South China Sea, a 64-element vertical array was utilized. The results demonstrate that the measured vertical spatial correlation coefficient aligns closely with the theoretical findings when wind-induced noise is predominant. The measured temporal correlation coefficient of narrowband noise exhibits a cosine function with gradual attenuation of the envelope, and the correlation radius remains independent of frequency. As the bandwidth increases, the measured broadband noise temporal correlation radius gradually decreases. Wind speed has minimal influence on the temporal and spatial correlation coefficients of wind-induced noise. In the presence of interferences such as ships and pulses, the measured temporal and spatial correlation coefficients of wind-induced noise exhibit larger values in certain intervals.Lastly, leveraging the characteristic that the temporal coherence radius of noise is significantly smaller than that of the line spectrum signal, a single-hydrophone cross-spectrum method is proposed to process the line spectrum signal. This approach effectively enhances the signal-to-noise ratio of the line spectrum.

Benefits of using ANSI/ASA S12.9 -2020/Part 7: “Measurement of environmental sound: Measurement of low-frequency noise and infrasound outdoors and in the presence of wind and indoors in occupied spaces.”

I was invited and honored by Dr. Paul Schomer to Chair working group S12/WG 54 for Part 7 of ANSI S12.9. The working group had 23 learned members all at the reasonable disposal of the Chair. At the start I knew the technical tasks that would have to be done and it would be a time-consuming process, at least a year; completion took over three years. Some of the fundamental tasks required were (a) Define and quantify wind-induced-noise (WIN) for standard wind screen measurements and with upgraded wind protection to lower WIN, (b) Define conversion corrections necessary between post-mounted above grade and ground plane mounted microphones, and (c) Define a repeatable technique for measuring pressure levels outside and inside structures to characterize noise reduction NR in 1/3 octave bands for the facade of the structure. These tasks were completed with much effort by numerous group members. The standard may be consulted for analyses and reference, particularly Annexes A through D, as well as for authoritarian standard purposes. This presentation will outline the many valuable procedures in the standard for measuring low frequency noise and infrasound.

Modeling sea surface noise in the presence of seamounts and ocean fronts using Nx2D and 3-D methods

This study focuses on modeling the ambient noise observed along a vertical line array in the presence of distributed surface sources and extreme bathymetric and oceanographic features. The distributed surface sources considered in this study include wind-induced noise, while the extreme bathymetric and oceanographic features comprise seamounts such as Atlantis II and the ocean front caused by the Gulf Stream. Directional vertical noise levels are modeled by computing the Green’s Function between the array elements and the distributed surface sources, estimating the average cross spectral density matrix, and calculating the plane wave response [1]. Green’s functions are computed using the Bellhop3-D ray tracing model [2] in both an Nx2D and full 3-D environment, and the resulting directional noise levels are compared. The results of this study will provide insights into the accuracy and effectiveness of the modeling methods used to predict ambient noise levels in such challenging environments, with particular emphasis on the contribution of seamounts to ambient noise. The implications of these results can be significant for thedesign and operation of underwater acoustic systems in similar environments.

DAS with telecommunication fibre-optic cable in urban areas can record storm-induced seismic noise

SUMMARY Extreme weather events threaten life and property in populated areas. Timely and precise weather event monitoring and risk assessment are critical, but can be hampered by limited meteorological stations in cities. Recent studies have shown that seismic stations are sensitive to storm-induced noise. This study aims to investigate the sensitivity of distributed acoustic sensing (DAS), a technology capable of turning existing optical fibres into dense seismic sensors, for recording storm-induced seismic noise. We analyse 4-month continuous DAS recordings (June–September 2021) from a 4.2-km-long underground fibre-optic array in State College, PA. We calibrate the DAS data by comparing it to various meteorological data (rainfall and wind speed) from nearby weather stations. We first show DAS-recorded low-frequency wind-induced noise (0.5–8 Hz) probably caused by light poles swaying in the wind, as observed resonant frequencies agree with theoretical natural frequencies of nearby light poles. We find a strong linear correlation between DAS energy and wind speed. We further characterize rain-induced noise. Detailed observations from two rain events: a moderate rain and a heavy rain from Hurricane Ida, suggest that rain-induced noise is not generated by direct raindrops hitting the ground. Instead, the low-frequency noise (2–8 Hz) is attributed to the acoustic noise generated by water flow in stormwater drainage systems. Strong high-frequency noise up to 125 Hz is likely related to the rapid rainwater filling from the surface to the drainage system during heavy rain. We show linear relations between rain-induced DAS energy and rainfall rate, where the slopes of relations are related to the volume of rainwater, suggesting the influence of surface water and rainwater flow in the drainage system on DAS signals. Our results show the possibility of using DAS-equipped pre-existing telecom fibre-optic cables for sensing windstorms and rainstorms in urban areas and their interactions with urban infrastructures.

Wind-induced noise estimation of wind speed and direction within urban microspaces: Characterizing flow condition of urban environments

In this work, the flow conditions within urban microspaces are predicted from wind-induced noise. Wind speed and direction are estimated by fitting the spatial coherence of the wind noise distribution among closely spaced microphones measurements to the Corcos model in the least squares sense. The estimated wind speed and direction are compared to measure results. The estimated flow conditions of the measured urban areas are discussed.

Characterizing flow conditions of urban environments from wind-induced noise measurements: A semi-empirical wind noise model of the University of the District of Columbia campus

In this work, the flow conditions within the University of the District of Columbia (UDC) urban campus are predicted from wind-induced noise. Wind-induced noise obtained from a collection of spatial distributed microphones are used to estimate the mean velocity airflow and wind noise distribution across the UDC campus. Wind speed and direction are estimated by fitting the second-order statistics of semi-empirical models of wind noise distribution from microphone measurements to analytical models in the least squares sense. The accuracy of the proposed is investigated for average microphone separation and time resolution. Comparisons of the wind speed and direction results to ultrasonic anemometer measurements are discussed.

Wind speed and direction estimation based on the spatial coherence of closely spaced microphones.

Wind-induced noise recorded with a compact microphone array can be exploited to infer the mean velocity of the free-field airflow. In this work, a model-based method to estimate the wind flow speed and direction is proposed that uses spectro-spatial correlations of closely spaced microphone signals. As shown in a recent work by the present authors, the normalized cross-power spectral density of flow-induced noise measured with closely spaced microphones, also referred to as the spatial coherence, can be approximated by a semi-empirical model, named the Corcos model. Due to the dependency of the Corcos model on the airflow velocity, the measured spatial coherence provides information on the sought quantity. Speed and direction can be resolved by fitting the measured spatial coherence to the analytical Corcos model in the least squares sense. The accuracy of the proposed method is investigated across a range of wind speed between 0.5 and 12 ms-1 and all directions, using observation lengths from 5 s to 1 h. The audio samples under test were recorded indoors and outdoors and labeled by an ultrasonic anemometer. The evaluation results show that the accuracy can be increased by reducing the time resolution.

Experimental and Numerical Analyses of Wind-Induced Noise in Two-Way Radios

The generation of wind noise of entrance microphone cavities owing to turbulent airflow is an inherent problem with radio telecommunication systems, such as two-way radios. It will lead to a pressure fluctuation which is highly unpleasant and would degrade a two-way radio communication. This research aims to understand the relationship between noise level and the flow structure of the different parameters to the occurrence of noise during communication using a two-way radio device. A noise measurement is conducted to analyse the sound pressure level (SPL) within a cavity, in which computational fluid dynamic(CFD) is used to investigate the flow behaviour on the various effects of cavity positions at P1, P2, P3, P4, and P5 and wind velocities of 0.75 m/s, 1.49 m/s, 2.24 m/s, 2.99 m/s and 3.75 m/s which corresponding to Reynolds number (Re) of 8694, 17389, 26083, 34777, and 43471 respectively. CFD result showed the presence of separation of the shear layer, the development of vortex shedding, the recirculation region and vorticity were present inside the edges of the cavity. SPL increased with an increase in wind velocity and, the cavity distance of P4. In the cavity position of P5, SPL is decreased due to the wind velocity exceeding the maximum level of a wind tunnel. Therefore, the cavity position of P5 is suitable for reducing wind noise. These parameters are significant for improving the design of two-way radio to reduce the noise during outdoor communication.

Cross-Spectral Density Sensitivity Kernels in Surface Noise Field

The main factors affecting the spatial characteristics of surface noise fields are changes in sound speed and sea surface boundary perturbations due to mesoscale ocean phenomena and wind-induced noise, respectively. This study derived the surface noise cross-spectral density sensitivity kernel for sound speed changes and local boundary perturbations and analyzed their effects on cross-spectral density. Numerical results show that the sound speed perturbations of any position in the entire observation plane changes the surface noise cross-spectral density function in surface noise with finite frequency. The cross-spectral density between two receivers in the vertical direction is the most sensitive to the sound speed changes of the region between two receivers. Additionally, the influence depends on the relationship between the wavelength of sound wave and the distance of two receivers. Scattering on the surface boundary perturbation would lead to fluctuations in the cross-spectral density function. When the boundary perturbation along the horizontal direction is distant from two receivers, the cross-spectral density sensitivity kernel for surface scattering oscillates, and the influence of boundary perturbation on the cross-spectral density function gradually weakens. Finally, the period of the cross-spectral density sensitivity kernel oscillations is a half wavelength of the sound wave.

Investigation of a microphone height correction for long-range wind farm noise measurements

In the measurement of wind farm noise, it is standard practice to mount outdoor microphones at a height of 1.5 m. On the other hand, measurements at this height can be affected by wind-induced noise, which has the potential to mask the noise of interest, particularly at low and infrasonic frequencies. Therefore, to minimise wind-induced noise, it is advantageous to measure on or below the ground, where the wind speed is close to zero. However, results from measurements taken at any height other than 1.5 m must be interpreted with caution, due to different interference effects between direct and ground-reflected waves at each location. This investigation explores the feasibility of using a prediction model based on Nord2000 algorithms to correct the 1/3-octave sound pressure level measured at ground level to obtain a representative value for a height of 1.5 m. The model takes into account phase changes due to the difference in travel-time for the direct and reflected rays and finite ground impedance, multiple source contributions and incoherence due to turbulence. The focus is on propagation distances greater than 2 km, where limited validation of existing propagation models has been attempted previously. Comparison is made between the model and measurement results obtained at four locations near a wind farm, where microphones were mounted at a height of 1.5 m and at ground level. A lack of agreement between measurements and the model indicates that the efficient and practical correction method considered here is not feasible for long-range wind farm measurements. Thus, it is recommended that wind farm noise is measured at both 1.5 m (for mid- to high-frequency noise) and at ground level (for low-frequency noise, which is more affected by wind).

Sub-Band Detector for Wind-Induced Noise

This study considers the problem of reliably detecting wind in portable devices such as mobile phones, personal digital assistants (PDA), tablet computers, and alike. A multi-microphone wind detector is presented that utilizes statistical analysis of microphone signals. This statistical analysis is used to quantify the discrepancy in dynamic behavior of the microphone signals. Empirical Distribution Function (EDF) is proposed to capture the dynamic behavior of each microphone signal, and the discrepancy in this behavior is quantified using mean absolute difference between the corresponding EDFs. A decision about wind presence is made separately for each chosen sub-band in order to avoid performing wind noise reduction in a part of audio spectrum which was not affected by wind-induced noise. The proposed wind detector demonstrates reliable detection of wind for each chosen sub-band in an exemplary mobile phone application. Performance evaluation confirms superiority of the proposed sub-band wind detector in terms of correct detection and false alarm compared to a state-of-the art wind detector.

On the Analysis of Wind-Induced Noise in Seismological Recordings

Atmospheric processes, ranging from microscale turbulence to severe storms on the synoptic scale, impact the continuous ground motion of the earth and have the potential to induce strong broad-band noise in seismological recordings. We designed a target-oriented experiment to quantify the influence of wind on ground motion velocity in the Dead Sea valley. For the period from March 2014 to February 2015, a seismological array, consisting of 15 three-component short-period and broad-band stations, was operated near Madaba, Jordan, complemented by one meteorological tower providing synchronized, continuous three-component measurements of wind speed. Results reveal a pronounced, predominantly linear increase of the logarithmic power of ground motion velocity with rising mean horizontal wind speed at all recording stations. Measurements in rough, mountainous terrain further identify a strong dependency of wind-induced noise on surface characteristics, such as topography and, therefore, demonstrate the necessity to consider wind direction as well. To assess the noise level of seismological recordings with respect to a dynamically changing wind field, we develop a methodology to account for the dependency of power spectral density of ground motion velocity on wind speed and wind direction for long, statistically significant periods. We further introduce the quantitative measure of the ground motion susceptibility to estimate the vulnerability of seismological recordings to the presence of wind.

Pressure spectra in turbulent flows in the inertial and the dissipation ranges.

Based on existing studies that provide the pressure spectra in turbulent flows from the asymptotic pressure structure function in the inertial range, this paper extends the pressure spectrum to the dissipation range by proposing a pressure structure function model that incorporates both the inertial and dissipation ranges. Existing experiment results were used to validate the proposed pressure structure function model first, and then the obtained pressure spectrum was compared with the simulation and measurement data in the literature and the wind-induced noise measured outdoors. All comparisons demonstrate that the pressure spectrum obtained from the proposed pressure structure function model can be used to estimate the pressure spectra in both the inertial and dissipation ranges in turbulent flows with a sufficiently large Reynolds number.

Wind-induced noise in a convective boundary layer

Wind-induced noise, as sensed by a screened microphone in the atmosphere, produces a highly varying noise floor. At low frequencies, this noise source may dominate the ambient noise spectrum and present a challenge for signal detection. The sensed noise is affected by several factors in the atmospheric convective boundary layer: the mean flow at the height of the microphone, turbulent eddy interaction with the windscreen, and pressure fluctuations within the turbulent flow. Recently, van den Berg (2006) compared measured wind noise to modeled spectra. In that study, several meteorological variables were inferred from fits of modeled wind noise spectra rather than from meteorological observations. If additional meteorological observations are collected, then it may be possible to conduct model validation. In addition to temperature, pressure, and wind velocity, the surface roughness length for momentum and the vertical temperature flux must be observed. Recent models of turbulent wind velocity, in the convective boundary layer, suggest that the planetary boundary layer height may also be an important variable for wind-induced noise. This study analyzes data collected in the Southwestern United States during a 2007 long-range sound propagation experiment. Wind noise data are compared against concurrent meteorological data and several wind-induced noise models.

Wind-induced noise reduction using a small two-channel microphone array

Wind-induced noise reduction using a small two-channel microphone array