Distribution Of Noise Sources Research Articles

Noise source localization using deep learning

Summary Ambient noise source localization is of great significance for estimating seismic noise source distribution, understanding source mechanisms and imaging subsurface structures. The commonly used methods for source localization, such as the matched field processing and the full-waveform inversion, are time-consuming and not applicable for time-lapse monitoring of the noise source distribution. We propose an efficient alternative of using deep learning for noise source localization. In the neural network, the input data are noise cross-correlation functions and the output are matrices containing the information of noise source distribution. It is assumed that the subsurface structure is a horizontally layered earth model and the model parameters are known. A wavefield superposition method is employed to efficiently simulate ambient noise data with quantities of local noise sources labelled as training datasets. We use a weighted binary cross-entropy loss function to address the prediction inaccuracy caused by a sparse label matrix during training. The proposed deep learning framework is validated by synthetic tests and two field data examples. The successful applications to locate an anthropogenic noise source and a carbon dioxide (CO2) degassing area demonstrate the accuracy and efficiency of the proposed deep learning method for noise source localization, which has great potential for monitoring the changes of the noise source distribution in a survey area.

Towards limited-domain full waveform ambient noise inversion

SUMMARY Ambient noise tomography is a well-established tomographic imaging technique but the effect that spatially variable noise sources have on the measurements remains challenging to account for. Full waveform ambient noise inversion has emerged recently as a promising solution but is computationally challenging since even distant noise sources can have an influence on the interstation correlation functions and therefore requires a prohibitively large numerical domain, beyond that of the tomographic region of interest. We investigate a new strategy that allows us to reduce the simulation domain while still being able to account for distant contributions. To allow nearby numerical sources to account for distant true sources, we introduce correlated sources and generate a time-dependent effective source distribution at the boundary of a small region of interest that excites the correlation wavefield of a larger domain. In a series of 2-D numerical simulations, we demonstrate that the proposed methodology with correlated sources is able to successfully represent a far-field source that is simultaneously present with nearby sources and the methodology also successfully results in a robustly estimated noise source distribution. Furthermore, we show how beamforming results can be used as prior information regarding the azimuthal variation of the ambient noise sources in helping determine the far-field noise distribution. These experiments provide insight into how to reduce the computational cost needed to perform full waveform ambient noise inversion, which is key to turning it into a viable tomographic technique. In addition, the presented experiments may help reduce source-induced bias in time-dependent monitoring applications.

Numerical Investigations on Phase Cancelation of Interaction Noise for Counter-Rotating Propellers

The large interaction tonal noise of counter-rotating propellers significantly restricts their application in civil aviation. A pair of counter-rotating propellers was simulated by the lattice Boltzmann method, and the far-field noise was predicted by the Ffowcs Williams and Hawkings analogy. Dynamic mode decomposition was introduced to analyze the surface pressure contribution to far-field noise and to provide insights on the cancellation mechanism of the noise source distribution for the interaction tone. It was found that the cancellation effect is closely related to the relative position between the front blade wake and rear blade element. By adjusting the rear blade sweep and, hence, changing the relative position, the interaction tone can be reduced effectively.

On the retrieval of body waves from ambient noise based on regional seismic arrays

SUMMARY Ambient noise technology can efficiently extract surface wave signals from seismic background noise and has been extensively utilized in imaging lithospheric structures. However, retrieving crustal body wave signals, such as PmP or SmS phases, still poses a challenge. Only a limited number of reports have successfully extracted these regional-scale body wave signals from ambient noise in only a few limited study areas. It remains unclear why these signals are difficult to retrieve from ambient noise data. To investigate the mechanism of recovering body wave signals in noise cross-correlations, we calculate cross-correlation functions at four regions and observe the similarity of the recovered body waves. Through a series of synthetic simulations, we demonstrate that the appearance of body wave signals in noise cross-correlations is closely related to the distribution of noise sources. Among these signals, the post-critical SmS wave proves to be the most readily recoverable from ambient noise data, primarily stemming from distant sources. In contrast, the recovery of P-wave requires the array to be in proximity to the sources. Our experiments also reveal that the main origin of PL waves is the multiple reflections of S-waves propagating in the crust.

Parallel-swath-array analysis of passive source surface waves based on beamforming

The detection of mined-out coal area remains a pivotal subject in geophysical prospecting and presents an urgent issue requiring resolution. A refined and effective approach to tackle this challenge involves conducting dispersion analysis on passive surface waves, which are derived from ambient noises. While classical passive surface wave methods, such as the Spatial Autocorrelation Method (SPAC), rely on spatial and time domain stationary assumptions, these can be difficult to fulfill. This is especially true when using ambient noises with frequencies >1 Hz, leading to a growing disparity between basic assumptions and actual scenario. To reduce this discrepancy, it's crucial to account for the non-stationary features of noise sources. In this study, we introduce a pioneering approach for parallel-swath-array analysis of passive source surface waves based on beamforming, making full use of non-stationary ambient noises. The parallel-swath array allows for efficient data collection and high-density spatial observation. The method's core concept involves: 1) The collection of noise data by a 2-D array arranged in three parallel lines; 2) The use of a plane-wave basis function to directly scan the original noise records in a time-segment mode within the time domain. These are conducive to unveil the azimuths and time-variant characteristics of the noise sources, resulting in accurate surface wave dispersion information. To ascertain the feasibility and effectiveness of this innovative method, we simulated passive surface wave records for a geological model, accommodating both time-invariant and time-variant distribution of noise sources. The results demonstrate that the method successfully reveals the time-invariant or time-variant characteristics of noise sources and the associated surface wave dispersion information. Simultaneously, we employ the preprocessed steepest-descent (PSD) algorithm to invert the dispersion curves, and the low-velocity layer in the numerical tests can be clearly revealed. In conclusion, we deployed this method in a coal mine situated in Northern China, which encompasses abandoned mined-out areas. This procedure effectively disclosed the intricate azimuthal properties of the noise sources, yielding high-resolution dispersion images. The inversion outcomes depicted a 2-D S-wave velocity section plunging to a depth of 60 m. By interpreting the low-velocity features of the mined-out area, we can accurately delineate its boundaries. The results of the interpretation align coherently with the findings from the drilling data, to verify the feasibility and effectiveness of parallel-swath-array analysis of passive source surface waves based on beamforming in detecting coal mined-out area under non-stationary ambient noises.

High Frequency Passive Surface Wave Dispersion Extraction by Linear Seismic Array Aligned with Noise Source Azimuth

Due to the uneven spatial and temporal distribution of noise sources, the dispersion data extracted from high-frequency (>1Hz) ambient noise data would be contaminated and biased. Based on the azimuth analysis of the noise sources, we propose a linear array data acquisition strategy that considers the noise source direction to get high quality dispersion data.

Determination of railway noise contribution based on noise source identification and acoustic transfer function

Environmental noise standards of noise for Japan's bullet trains, known as Shinkansen, are among the most stringent in the world. To reduce train noise and meet these standards, the contribution ratio of each noise source to the total noise at the observation point provisioned by the Japanese government, 25 m from the nearest track must be determined. Although previous studies have determined the contribution ratio using multiple omnidirectional microphones and a 1-dimensional microphone array positioned at the observation point, we propose a new method to evaluate the contribution ratio by combining the noise source identification with an acoustic experiment. The microphone array clearly measures the noise source distribution around a vehicle using signal processing of the deconvolution algorithm, indicating that bogies and pantographs are the dominant aerodynamic noise sources. The transfer function of the radiated sound between the sources and observation point was determined in the acoustic model experiment with a viaduct and noise barrier. The contribution ratio obtained should be useful in assessing the noise reduction from shape modification.

Sequencing Seismic Noise Correlations for Improving Surface Wave Retrieval and Characterizing Noise Sources

Abstract Cross-correlating continuous seismic data is a commonly employed technique to extract coherent signals to image and monitor the subsurface. However, due largely to site effects and poorly characterized noise sources in oceanic environments, its application to ocean-bottom seismometer (OBS) recordings often requires additional processing. In this contribution, we propose a method to improve the quality of the retrieved surface waves from OBS data and characterize the noise sources. We first cluster the pre-stack noise cross-correlation functions (NCFs) based on a sequencing algorithm, followed by selectively stacking those consisting of coherent and stable signals that are consistent with predicted surface-wave arrival times. Synthetic tests show that the sequenced NCFs can be used to recover the spatial and temporal distribution of noise sources. Applying the method to an OBS array offshore California increases the signal-to-noise ratios of the obtained Rayleigh waves. In addition, we find that the annual temporal distribution of selected NCFs with frequencies ranging from 0.04 to 0.1 Hz is nearly homogeneous during the recording period. In contrast, many NCFs excluded for stacking are temporally clustered. This method has the potential to be applied to other OBS recordings or possibly onland deployments, thus helping to obtain high-quality surface waves and to analyze temporal noise source characteristics.

Noise correlation analysis: the role of the inflection points in the formation of zero-time waves

SUMMARY The cross-correlation function (CCF) of seismic noise recorded at two stations often exhibits a prominent burst of energy near zero time. However, the excitation mechanism of such unexpected signals remains unclear. In this study, we demonstrate that this phenomenon arises from constructive interference of body waves radiating from sources near the mid-vertical plane between two receivers. This interference is driven by the occurrence of an inflection point effect in the traveltime difference between waves reaching the two receivers. When noise source distribution is asymmetric, the cumulative effect of such sources results in the generation of zero-time waves. It is noteworthy that a noise source distribution that is either uniform or follows a cosϕ pattern, with ϕ denoting the azimuth from the centre of the receiver pair, can counteract the formation of these waves. Additionally, our investigation reveals that this constructive interference does not occur in the correlation of 2-D surface waves. We used numerical simulation to support our findings. In conclusion, this study offers a theoretical explanation for the emergence of zero-time waves on the CCF and provides efficient means of investigating the extraction of inter-receiver waves with uneven noise source distribution.

Influence of nozzle external geometry on the emission of screech tones

The effect of external nozzle geometry on the emission of screech tones was studied experimentally. Four conical reflector surfaces, with half-angles ranging from 60° to 90°, were installed around the exit of a round convergent nozzle. The investigation focused on two closely spaced fully-expanded Mach numbers, M j = 1.32 and 1.34. The acoustic far-field was surveyed by a microphone phased array that included a continuously-scanning microphone, the latter enabling high spatial resolution. The isolated jets contained well-known screech mode B and its harmonics. Addition of the reflectors caused significant changes in the modal emission pattern, with tones traditionally linked to mode C occurring at M j = 1.34 but not at M j = 1.32. Tonal components associated with new modes E and F emerge at both Mach numbers when the cone half-angle is 60° or 70°. The noise source distribution generally elongates with decreasing cone angle. Some modes show clear scattering from the reflectors, while others do not. The study underscores the complexity that initial conditions can impart on the modal structure of screech and demonstrates the capability of the continuous-scan beamforming technique in resolving fine features of the source.

Speech perception in modulated noise assessed in bimodal CI users.

Although good speech perception in quiet is achievable with cochlear implants (CIs), speech perception in noise is severely impaired compared to normal hearing (NH). In the case of abimodal CI fitting with ahearing aid (HA) in the opposite ear, the amount of residual acoustic hearing influences speech perception in noise. The aim of this work was to investigate speech perception in noise in agroup of bimodal CI users and compare the results to age-matched HA users and people without subjective hearing loss, as well as with ayoung NH group. Study participants comprised 19bimodal CI users, 39HA users, and 40subjectively NH subjects in the age group 60-90years and 14young NH subjects. Speech reception thresholds (SRTs) in noise were adaptively measured using the Oldenburg Sentence Test for the two spatial test conditions S0N0 (speech and noise from the front) and multisource-noise field (MSNF; speech from the front, four spatially distributed noise sources) in continuous noise of the Oldenburg Sentence Test (Ol-noise) and amplitude-modulated Fastl noise (Fastl-noise). With increasing hearing loss, the median SRT worsened significantly in all conditions. In test condition S0N0, the SRT of the CI group was 5.6 dB worse in Ol-noise than in the young NH group (mean age 26.4years) and 22.5 dB worse in Fastl-noise; in MSNF, the differences were 6.6 dB (Ol-noise) and 17.3 dB (Fastl-noise), respectively. In the young NH group, median SRT in condition S0N0 improved by 11 dB due to gap listening; in the older NH group, SRTs improved by only 3.1 dB. In the HA and bimodal CI groups there was no gap listening effect and SRTs in Fastl-noise were even worse than in Ol-noise. With increasing hearing loss, speech perception in modulated noise is even more impaired than in continuous noise.

Distributed acoustic sensing for shallow structure imaging using mechanical noise: A case study in Guangzhou, China

Distributed Acoustic Sensing (DAS) is a novel seismic detection technology that transforms fiber-optic cables into densely sampled seismic stations, showing immense potential in both urban seismology and the oil and gas industry. We deployed a ~ 182-m-long single-core fiber-optic cable in a campus under construction to record human activity and demonstrated the application for seismic imaging. The spectrogram analysis revealed significant differences in ambient noise between the daytime and nighttime at the construction site. During the daytime, the noise energy exhibited dominant frequencies ranging from 2 to 11 Hz, approximately one order of magnitude higher than that at night, which had frequencies ranging from 2 to 5 Hz. Beamforming analysis demonstrated that noise sources exhibited distinct directional characteristics and propagation velocities during daytime and nighttime periods. We extracted the cross-correlation functions between DAS channels from the mechanical noise generated by a large excavator and enhanced signal-to-noise ratio by using the phase-weighted stacking method. The multichannel analysis of surface waves (MASW) method was then employed to obtain 2D near-surface shear-wave velocity. Based on five 60-m-deep boreholes drilled along the DAS array, we established the correlation between shear-wave velocity information and shallow structure. We obtained the unbiased cross-correlation function in the presence of continuous mechanical noise along the DAS array direction, demonstrating the importance of site noise source distribution analysis in ambient noise tomography. Our research is informative for research related to the construction of accurate, high-resolution near-surface shear wave velocity models.

Weighted stacking of ambient noise correlations based on the coherency of 3C data

Seismic interferometry (SI) is widely used in imaging subsurface structures at different scales by extracting empirical Green's functions (EGFs) of surface wave propagation from ambient noise. The EGFs may be misestimated, however, because the anisotropic distribution of noise sources violates the SI's basic assumption of energy equipartitioning. A common solution is to stack all short-duration noise cross-correlation functions (NCFs) over a long period of time to attenuate the effect of anisotropic noise sources. The effectiveness of the common method is limited by the time of observation, and it may even be counterproductive. The influence of anisotropic noise sources may be reinforced if these sources possess strong energy. To obtain reliable EGFs, we develop a new weighted stack method named the components-coherency-weighted stack (CCWS). We calculate the coherency of different components of noise recorded by a single station to scan the azimuth of the main source in one segment. We select the segments according to the azimuth for NCF computation and then stack the NCFs with a weight relevant to the coherency. We first test the method on simulated data containing strong azimuthal noise sources and show that our method yields high quality EGFs. The method is then used for two real data examples at a regional scale of hundreds of kilometers and an engineering scale of tens of meters. Two examples confirm the ability of our approach to improve the EGFs and its applicability at different scales.

Investigation of electric vehicle noise sources on low-noise road surfaces

Electric vehicles (EVs) constitute an increasing share of the vehicle fleet, in particular regarding light vehicles. This ratio may be significantly enhanced in urban areas that favour access to low-emission vehicles. Acknowledged to be quieter than conventional vehicles due to a lower propulsion noise, EVs feature a comparatively heightened tyre-road noise contribution, further reduction of which can be achieved by selecting appropriate low-noise road surfaces. These factors may result in modified noise source distributions on the vehicles. In the framework of the LIFE E-VIA project, noise source contributions have been investigated on several light EVs from different segments on a reference ISO road surface, by using a microphone array with dedicated processing. Wide ranges of speeds and driving conditions were considered. In a second step, particular focus has been placed on the road surfaces, comparing the noise sources of selected EVs either driving on the ISO road surface or on low-noise prototypes optimized for EVs and developed within the project. These are two similar versions of a very thin asphalt concrete 0/6, one containing crumb rubber. The presentation gives an overview of the EV noise source behaviour and their ranking with regard to the various situations tested in the project.

Prediction of Shipping Noise in Range-Dependent Environments

A prediction model for shipping noise in range-dependent environments based on coupled-mode theory is presented, as an enhancement to existing adiabatic normal-mode approaches without a significant increase in computational effort. Emphasis is placed on the categorization of environmental changes and precalculation and storage of eigenvalues, eigenfunctions and coupling matrices, such that they can be looked up and restored to efficiently compute the acoustic field of arbitrary noise source distributions over a given sea area. Taking into account that the water depth is the primary factor determining the number of propagating modes for a particular frequency, coupling is applied only in the case of changing bathymetry, whereas changes in the water sound-speed profile and/or the geoacoustic characteristics are treated adiabatically. Examples of noise calculations are given for benchmark setups in the Eastern Mediterranean Sea and comparisons with fully adiabatic predictions are drawn. Moreover, the effect of applying range propagation limitations in a numerical propagation model for shipping noise predictions is demonstrated.

SANS: Publicly Available Daily Multi‐Scale Seismic Ambient Noise Source Maps

AbstractSeismic ambient noise sources have received increased attention recently, creating new possibilities to study the Earth's subsurface and the atmosphere‐ocean‐solid Earth coupling. In efforts to locate such noise sources using nonlinear finite‐frequency inversions, methodological developments such as pre‐computed wavefields and spatially variable grids were necessary. These make inversions feasible for the secondary microseismic sources in a frequency range up to 0.2 Hz on a daily basis. By obtaining a starting model for the inversion using Matched Field Processing (MFP) we are able to further steer the inversion toward acceptable global noise source models and improve the final result. Analysis of 1 year of daily inversions shows the seasonal variations of the secondary microseisms and their dependence on the atmosphere‐ocean‐solid Earth coupling due to storm‐induced ocean waves. We present a web framework, seismic ambient noise sources (SANS, sans.ethz.ch), where daily regional‐ to global‐scale SANS maps for the secondary microseisms are made available to the public. This enables the implementation of time‐variable noise source distributions into full‐waveform ambient noise tomography and time‐dependent subsurface monitoring methods. Additionally, it can act as a reference for other studies that locate secondary microseismic sources on a larger scale.

Ambient noise autocorrelation scheme for imaging theP-wave reflectivity of the lithosphere

SUMMARYAmbient noise autocorrelations can be used to reconstruct the seismic reflection response of the Earth structure beneath single stations using continuous recordings without the need for either active sources or earthquakes. In the last decade, this technique has emerged as an inexpensive approach with the potential to provide similar information to that from the classical receiver function (RF) analysis. Previous studies have located and mapped discontinuities at different crustal depths with ambient noise autocorrelations by applying different processing techniques. An ambient noise autocorrelation function (ACF) provides the body-wave reflectivity of the local structure, assuming a homogeneous distribution of noise sources. However, an effective method design is required in order to determine a reliable reflection response. Here, we review the theory behind the ambient noise ACF method and design a workflow to obtain the P-wave reflectivity with a special focus on the Moho depth. In particular, we calculate a smooth function to fit and subtract the zero-lag component in the time domain, that is, the large-amplitude signal near 0 lag time in the ACF. The zero-lag component can interfere with the reflection component, so its removal allows us to increase the frequency band to use. We bandpass filter the ACFs between 1 and 6 s. We also derive and apply a phase shift correction in the ACFs due to the integration of a homogeneously distributed noise field dominated by distant sources from deep below, such as teleseismic sources. Both linear and nonlinear, phase-weighted stacks are used. Linear stacking is used to identify the main interfaces since it ensures the linearity of the processing steps; nevertheless, nonlinear, phase-weighted stacking help validate the coherent signals. We test and apply our method to continuous vertical recordings from three stations in Ireland and five stations in different cratons and obtain clear P-wave reflection from the Moho and other crustal and upper-mantle discontinuities in most cases. However, noise coming from local heterogeneities, non-homogeneous distribution of the ambient noise sources or instrumental noise is also expected. Therefore, additional, a priori information is desirable to help identify key phases in single ACFs. We compute synthetic ACFs using P-wave velocity (VP) models from controlled-source profiles in Ireland. The relatively complex ACF traces obtained at the stations in Ireland show a close data-synthetic match for the Moho and mid-crustal discontinuities. The ACF traces from the stations in different cratons are directly compared with receiver functions showing overall agreement and offering complementary information on the origin of the signal.

Enhancing noise sources in stationary-phase zones for accurate phase-velocity estimation of high-frequency surface waves

Passive surface-wave methods are appealing tools for their ability to noninvasively obtain shear-wave velocity with high accuracy and low costs. A linear array of stations is widely adopted in urban areas for its convenient deployments and efficient utilization of ambient noise energy from stationary-phase zones (SPZs), which contributes the most to surface-wave retrieval. However, noise sources in nonstationary-phase zones may threaten the reliability of velocity estimation when they possess strong energy. To obtain reliable phase-velocity estimation of high-frequency surface waves (>1 Hz), we enhance the contribution of noise sources in SPZs by using the multichannel-coherency-weighted stack (MCWS) method for the stacking of noise crosscorrelation functions and dispersion spectra. We model a nonuniform source distribution with strong offline sources. The seismic interferometry (SI) and passive multichannel analysis of surface waves (PMASW) methods overestimate velocities at lower frequencies (<5 Hz), whereas phase velocities of short wavelengths are relatively accurate. The true velocities of short wavelengths are then set as the velocity scanning range for MCWS, and the waves whose apparent velocities lie within the scanning range would be emphasized by MCWS. Noise sources in SPZs are enhanced because the apparent velocities of waves from other noise sources are higher and not in the scanning range. After using MCWS, the phase-velocity estimations of SI and PMASW are consistent with the theoretical dispersion curve. A field data example at a crossroads demonstrates that uneven source distributions might cause serious artifacts and the feasibility of our method is again confirmed. In addition, the enhancement of noise sources in SPZs is verified through noise source distribution imaging by a matched field processing technique.

Experimental Study on the Noise Evolution of a Horizontal Axis Icing Wind Turbine Based on a Small Microphone Array

In recent years, the global energy mix is shifting towards sustainable energy systems due to the energy crisis and the prominence of ecological climate change. Wind energy resources are abundant in cold regions, and wind turbines are increasingly operating in cold regions with wet natural environments, increasing the risk of wind turbine blade icing. To address the problem of noise source distribution and the frequency characteristic variation of wind turbines in natural icing environments, this paper uses a 112-channel microphone array to acquire the acoustic signals of a horizontal axis wind turbine with a diameter of 2.45m. Using the beamforming technique, the wind turbine noise evolution law characteristics under natural icing environment were studied by field experiments, and the noise source distribution and noise increase in different frequency bands under different icing mass and positions and different angles of attack were analyzed in detail. The results show that under the leading-edge and windward-side icing, the noise source gradually moves toward the blade tip along the spanwise direction with the increase in ice mass. In addition, the total sound pressure level at 460 r/min, 520 r/min, 580 r/min, and 640 r/min are increased by 0.82 dB, 0.85 dB, 0.91 dB, and 0.95 dB, respectively for the leading-edge icing condition in comparison with the uniform icing over the windward side of the blade.

Overview of ocean ambient noise interferometry – Theory and simulation

Ambient noise interferometry is a passive acoustic technique for environment characterization. The technique uses coherent ambient sound to approximate the Green’s function between two sensors. It has previously been used in ocean acoustics to passively estimate water temperature, sound-speed structure, and mode shapes as well as for sensor localization. Since this technique utilizes the ambient noise field, whose characteristics are often unknown, understanding the effects of non-isotropic ambient sound is important for ambient noise interferometry. In this talk, an overview of the theoretical literature for noise interferometry will be presented with a specific emphasis on the effects of non-isotropic ocean noise source distributions. Additionally, simulations that explore the emergence of the Green’s function will be presented. Specifically, sound source distributions and environmental parameters such as sound speed profile will be explored. Lastly, the implications of these works on the possibilities and limitations of ambient noise interferometry will be discussed. [Work supported by the ONR.]