Noise Source Localization Research Articles

Influence of emitter's position in the field of view of the acoustic camera and ground reflection in sound source localization with beamforming

Acoustic cameras are powerful tools that combine a video camera with a microphone array to locate noise sources. Different beamforming techniques can be applied to the acquired sound signals, allowing to visualize noise or distinguish the contribution of multiple different sources even emitting simultaneously. A procedure has been previously developed by the authors for the analytical analysis of the output images of the acoustic cameras. In fact, output images contain only visual information on the origin of the sound in the visual field of the camera, without providing analytical information about their position. The procedure allows to quantify the localized position and also evaluate the distance from the real emission point when know, making possible comparison between different acoustic camera or different beamforming algorithms. In the present work, the aforementioned procedure is applied to test measurements carried out with a known emitter in an open field to evaluate the effect that source's height from the ground and position in the field of view have in the localization with beamforming techniques.

Noise Source Diagnosis Method Based on Transfer Path Analysis and Neural Network

Clarifying the noise source and the contribution of each path is essential for the system’s noise control. The auxiliary converter cabinet, which is a crucial component of rail transportation, has numerous intricate noise sources. The contribution of each path point must be inverted-solved using known transfer functions and target point test values when identifying noise sources. This article suggests a method for diagnosing noise using transfer path analysis and neural networks (TPA-NN). Firstly, the principle and scheme for analyzing the transmission path of the converter cabinet are proposed. The transfer function of each path is obtained by selecting suitable path points, reference points, and target points for air and structure acoustic vibration experiments. The external target point data are then combined with the neural network’s linear fitting function, and the contribution of each path is used as an output for network training while some path point contributions are rebuilt. The results indicate that the method’s outcomes are most accurate when the converter cabinet’s path point is 13 and the target point is 6. This approach offers an innovative technique for locating noise sources in intricate systems.

Numerical simulation and prediction of aerodynamic noise of high-speed trains

In order to improve the efficiency of high-speed train aerodynamic noise analysis and provide a feasible method for aerodynamic noise prediction, the aerodynamic noise and its influencing factors are analyzed from the perspective of the total energy (sound power) radiated to the far field per unit time by the aerodynamic fundamental noise sources (monopole, dipole and quadrupole sources). A full-scale and a 1:8 scale-down computational fluid dynamics model of a high-speed train are established. The far-field sound pressure level at several receivers and velocities is calculated by using the transient large eddy simulation and the FW-H equation. The numerical simulation results are used to predict the aerodynamic noise under specified working conditions. The research work can achieve the prediction of aerodynamic noise at other velocities using noise data at known velocities on the same noise source case, as well as the prediction of aerodynamic noise of full-scale model using data of scale-down model, and is applicable to either bogies as local noise sources or the complete vehicle as a noise source. The maximum error between the prediction and simulation result is 0.33 dBA under various working conditions, which meets the engineering calculation requirements.

An application of dereverberation and multiplicative beamforming techniques for imaging noise sources generated by boat engines

This paper demonstrates the application of a dereverberation algorithm for localizing noise sources emitted from two-stroke boat engines in three dimensions domain. The engines considered have a maximum RPM of 1500 and 1200 cc. It is important to note that these engines are operated with both petrol and CNG. The investigation primarily focuses on the noise generated under various loading conditions and aims to differentiate the noise characteristics between petrol and CNG engine operations. The dereverberation algorithm is applied to enhance the accuracy of noise source localization in this study, it involves filtering an approximate optimal window width to retain data related to the direct field while removing reflections through multiplication with an appropriate Hanning window. The analysis showed that the dereverberation algorithm effectively improves the imaging source map compared to conventional beamforming maps in the 3-D domain. To compute the beamforming output, data has been recorded from five different sides of the engine, and the multiplicative beamforming technique is employed. The findings highlight the significance of dereverberation and multiplicative beamforming techniques in accurately localizing noise sources in boat engine applications.

Challenges in measuring and quantifying sonic booms from Falcon-9 booster landings

Sonic booms from Falcon-9 booster landings contribute to the overall noise of the vehicle, but obtaining high-fidelity acoustical measurements and robust metric calculations of each sonic boom pose several challenges. This paper discusses three such challenges: sonic boom metric variability from differences in vehicle trajectory and meteorology, poor low-frequency response of low-sensitivity microphones, and contamination of the sonic boom by the landing burn noise. To quantify the variability between measurements, boom metrics are compared across four separate launches from Vandenberg Space Force Base. Boom metrics calculated from microphone stations at the same location differ by as much as 10 dB from launch to launch. Next, a digital pole-shift filter helps correct the low-frequency response of low-sensitivity microphones near the pad. These filters are adjusted so the waveforms more closely match those from microphones with a superior low-frequency response. Last, to obtain a clean sonic boom waveform, tracking the noise source location and peak frequency may help to distinguish where the sonic boom ends and landing burn noise starts. However, due to similar frequency content and close spacing in time, separating the boom from the landing burn noise near the pad remains a challenge for some booms. [Work supported by USACE.]

What’s that noise—Found it! Sometimes

A few case studies involving investigation of mystery noise sources are presented. These address techniques used to identify the cause of complaints, locate noise sources amidst competing noise, and compare predicted sound levels to measured sound levels. The presentation will discuss mysteries solved, our approach to noise control recommendations, and lessons learned. Interesting cases include investigation of a tone generated by an electrical power transmission line pole, office noise control involving malfunctioning HVAC systems, and noise source identification within a quiet multi-family residence.

Improving the quality of high-frequency surface waves retrieved from ultrashort traffic-induced noise based on eigenvalue selection

SUMMARY Stacking cross-correlations of time windows from continuous long-duration noise data is an effective solution to improve the quality of retrieved high-frequency (>1 Hz) surface waves and the accuracy of dispersion energy. The observation duration, however, is usually limited due to traffic control, making it difficult for ambient noise sources to fulfill the requirement of uniform distribution. Additionally, strong human-related noise sources exist near survey lines deployed along urban roads, which often act as interfering sources, such as local noise sources located in the non-stationary-phase zones. Local noise sources cause spurious arrivals in cross-correlations, degrade signal-to-noise ratio (SNR) of retrieved surface waves and distort their dispersion energy. To attenuate these adverse effects and improve the quality of surface waves retrieved from ultrashort noise data, we perform the eigendecomposition technique on the cross-spectral density matrix (CSDM) and apply a Wiener filter on the decomposed eigenvectors. The correct eigenvalues and the corresponding filtered eigenvectors are selected to reconstruct the CSDM related to stationary-phase sources based on the matched-field processing outputs. This procedure significantly suppresses the backpropagated signals and efficiently recovers surface waves by improving the contribution of the stationary-phase sources. We validate our scheme on a synthetic test and two practical applications and show that we obtain higher-SNR virtual shot gathers and higher-quality surface-wave dispersion images compared to seismic interferometry. Our scheme can be a new alternative technique to conduct passive seismic surveys in densely populated urban environments without being affected by local noise sources.

Beamforming with modified steering vectors for jet noise source location

Prof. Krish Ahuja has a longstanding interest in jet noise source location. His work in this area is grounded in the idea that if the assumed source location is correct, then the sound should obey the inverse square law relative to that point and the phase should be constant along lines originating at that point. He applied this with, conceptually, one microphone in 1985 and two microphones in 1998. In 2006 he commissioned a beamforming system, Array 48, from OptiNav, Inc. His student, Nick Breen, used this to measure subsonic jet noise source location in detail. The NASA-Glenn Research Center also purchased an Array 48. In the current work, a jet noise data set measured by Gary Podboy using Glenn’s array in 2008 is revisited with a new beamforming algorithm, Robust Functional Beamforming, to further support Tam’s two-source model and Breen’s source location. Beamforming with modified steering vectors is performed to measure the parameters of the wavepacket source model from the far field. This process suggested replacing the wavepacket spatial length parameter with a temporal lifetime parameter. Another steering vector modification aimed to measure modes with odd spinning order. It seems to have found them at an apparent location 10 jet diameters removed from the jet, laterally. This is tentatively interpreted as a Mach radius phenomenon like one observed by Csaba Horvath at NASA-Glenn, also using Array 48, to study counter-rotating propeller noise. In an observation unrelated to beamforming, the excess noise measured at 40° from the jet axis as compared with the 90° angle, is fully contained in the first few cross spectral matrix eigenvalues, or Spectral Proper Orthogonal Decomposition modes, in some cases.

Use of Acoustic Camera for Noise Sources Localization and Noise Reduction in the Industrial Plant

The paper presents results of the localization of main noise sources in the industrial plant. Identification of main noise sources was made with an acoustic camera using Beamforming Method. Parallel to the measurements by means of the acoustic camera, sound level measurements on the main noise sources have been performed. Based on the calculations, prediction regarding the noise emission at residential buildings located near to the plant has been determined. Acoustic noise maps have been performed with LEQ Professional software, which includes the 3D geometry of the buildings inside the plant. It has been established that, after introduction of noise reduction measures in the plant, the noise levels at the observation points in the residential area meets the limit values.

Long-Term Perceived Benefit of Pediatric Cochlear Implant Users with Unilateral Hearing Loss.

To assess the perceived benefit of cochlear implant (CI) use for children with unilateral hearing loss (UHL) and evaluate whether perceived abilities are associated with performance on measures of speech recognition and spatial hearing. Nineteen children with moderate-to-profound UHL underwent cochlear implantation. The Speech Spatial and Qualities of Hearing Questionnaire modified for children (SSQ-C) were completed by parental proxy pre-operatively and at 3, 6, 9, 12, 18, and 24 months post-activation. Linear mixed models evaluated perceived benefits over the study period. Pearson correlations assessed the association between subjective report and performance on measures of word recognition with the CI alone and spatial hearing (speech recognition in spatially-separated noise and sound source localization) in the combined condition (CI plus contralateral ear). For the SSQ-C, parents reported significant improvements with CI use as compared to pre-operative perceptions (p < 0.001); improved perceptions were either maintained or continued to improve over the 2-year post-activation period. Perceived benefit did not significantly correlate with word recognition with the CI alone or spatial hearing outcomes in the combined condition. Families of children with UHL observed benefits of CI use early after cochlear implantation that was maintained with long-term device use. Responses to subjective measures may broaden our understanding of the experiences of pediatric CI users with UHL in addition to outcomes on typical measures of CI performance. 3 Laryngoscope, 134:919-925, 2024.

Non-negative aeroacoustic source contributions to radiated sound power

A new approach that determines the contribution of aeroacoustic sources to sound power is presented. The method combines the Lighthill source distribution with an acoustic impedance matrix constructed from radiation kernels of the free-field Green's function. To demonstrate the technique, the flow noise produced by a pair of co-rotating vortices is examined. Results are initially compared with those obtained using Möhring's analogy of two-dimensional vortex sound radiation. The contribution to sound power for each component of the Lighthill tensor is presented for a range of wave numbers and vortex separation distances. For acoustically compact cases, the aeroacoustic source contributions for the diagonal components of the Lighthill tensor show a similar trend observed in sound maps for longitudinal quadruples. In contrast to the acoustically compact cases where the central focal area is mostly unchanged with variation in Mach number, significant variation in the focal areas occurs for non-acoustically compact cases. Using the aeroacoustic source contribution technique, the nature and location of dominant flow noise sources to sound power can be identified.

High precision localisation of the sources of noise of a bent-axis motor

The hydraulic motor will generate noise in operation and it has fluid-structure coupling and compact internal structure. The sound intensity measurement is difficult to distinguish the noise sources of motor. In this paper, a high-precision localization method for noise sources of bent-axis motor is studied to improve the resolution of the sound intensity images to locate noise sources accurately. Firstly, the structural characteristics of the motor are analyzed, and the sound intensity images are obtained through the experiment. Then the high-resolution optimization method based on compressed sensing is designed according to the characteristics of the sound intensity field. Finally, the sound intensity images with high resolution are constructed. The high-resolution images can distinguish the position of the prominent points, and the error is less than 0.4 dB. The identification distance of noise sources can reach 30 mm, and it breaks through the highest resolution of the traditional sound intensity test.

Joint Noise Model Learning and Source Localization With Unknown Transmit Power

Instead of assuming the accurate noise model and transmit power, we address the received signal strength (RSS) localization problem under a more practical assumption that the exact noise model and transmit power are unavailable. In this letter, we propose to use a universal mixture of Gaussian (MoG) distribution to model the unknown noise due to the fact that MoG distribution can adaptively fit any distribution by adjusting the involved parameters. We propose a novel variational inference framework to achieve joint automatical noise model learning and target localization with unknown transmit power. Numerical experiments are conducted to prove the robustness and effectiveness of the proposed algorithm.

Suboptimal controller design of global active noise control system for various acoustic environments

Conventional active noise control (ANC) systems in enclosed spaces are not easy to implement experimentally because they require a large number of microphones to measure sound pressure in global areas. Even if such systems are possible, if there are any changes in the locations of noise sources or surrounding objects, or if ANC system moves to another enclosed space, an expensive and time-consuming experimental calibration is again required. Implementation of global ANC in enclosed spaces is thus difficult. Therefore, we designed a global ANC system that can be used in various acoustic environments. The main idea involves suboptimal open-loop controller design in the free field. By using an open-loop controller, a controller calibrated once can be used in various acoustic environments. A controller designed in the free field derive a suboptimal solution without bias toward a specific acoustic environment. For controller design in the free field, we propose an experimental calibration approach in which the arrangement and the number of control speakers and microphones are determined by the frequency range and radiation pattern of the noise source. We conducted simulations and experiments to show that the designed controller in the free field is sufficiently effective in other enclosed spaces.

Localization and Ranking of Aircraft Noise Sources in Flight Tests and Comparison with Acoustic Measurements of a Large-Scale Wing Model

Localization and Ranking of Aircraft Noise Sources in Flight Tests and Comparison with Acoustic Measurements of a Large-Scale Wing Model

A Low Frequency Noise Source Localization and Identification Method Based on a Virtual Open Spherical Vector Microphone Array

Aiming at the problem of poor spatial resolution of low-frequency noise sources in a small-aperture spherical microphone array (SMA), this paper proposes a method for localizing and identifying low-frequency noise sources based on virtual-vector open SMA (‘p+v’ joint processing method of pressure and velocity). Firstly, a virtual open SMA with a larger aperture is obtained using a virtual array extrapolation method. In this method, the virtual SMA and the actual SMA are regarded as a dual-radius SMA, and velocity information is obtained using finite difference elements of the same direction (azimuth and elevation) array of the virtual and actual SMA. At the same time, the sound pressure at the velocity position is obtained using the virtual SMA extrapolation method and the virtual vector array element SMA, whereby both velocity and sound pressure information is obtained. Finally, the vector signal processing technology is introduced into the generalized inverse beamforming algorithm (GIB). After determining the vector transfer function of the ‘p+v’ joint processing mode, a low-frequency-noise-source localization and identification method based on the vector signal processing GIB is proposed. The simulation and experiment results show that a virtual SMA with a large aperture can be obtained using a virtual array extrapolation method, and the GIB with sound pressure and velocity joint processing has a better spatial resolution.

Insights into the conditions of application of noise-based spectral ratios in a highly industrialized area: a case study in the French Rhone Valley

SUMMARY The local ground motion amplification related to the geology at a specific site (i.e. the so-called site effects) may be classically quantified through the SSR (standard spectral ratio) technique applied on earthquake recordings. However, such a quantification might be challenging to carry out in low-to-moderate seismicity regions. Methods based on background ambient noise, such as noise-based standard spectral ratio (SSRn), might be of great interest in these areas. But noise-derived amplification is particularly sensitive to local anthropogenic sources, which may introduce biases in the evaluation of site effects by dominating the geological effects, especially for frequencies higher than 1 Hz. A hybrid approach (SSRh), developed to reduce biases in noise-based spectral ratios by combining classical earthquake-based spectral ratio (SSR) and SSRn, was recently introduced and relies on a site reference. We here investigate the applicability of SSRn and SSRh in a heavily industrialized environment in the Tricastin Valley (south-east France), where critical facilities are located. We continuously recorded ambient noise from 2020 February to March on a 400-sensor seismic array covering an area of about 10 km by 10 km. We demonstrate that SSRn and SSRh computed below 1 Hz are able to reproduce amplification factors provided by SSR. By contrast, at frequencies higher than 1 Hz, SSRn strongly deviates from SSR. SSRh shows closer results to SSR but presents a dependence to the choice of the local site reference, thereby questioning the possibility to use SSRh blindly to estimate the local amplification in our context. These discrepancies reflect the impact of local anthropogenic sources. We therefore introduced a two-step workflow to mitigate the influence of local sources. The first step is to define a characteristic time window to optimally isolate significant transient signals. The second step consists in selecting the time segments that do not contain these transients with a clustering-based approach. By applying this workflow, we were able to remove some strong anthropogenic transient signals likely to be generated by local sources at some sites and therefore to locally improve the amplification assessment through noise-based spectral ratios. However, stationary sources, whose impact cannot be removed through our procedure, remain a major issue. This study provides some insights into the application of SSRn and SSRh in noisy industrialized areas, especially regarding the impact of local noise sources. It illustrates the difficulty of having a procedure for mitigating the impact of these sources that is efficient everywhere inside such a complex anthropized environment, where different types of sources (including stationary sources) cohabit.

A hybrid compressive sensing approach to noise source visualization: Application to a diesel engine

To identify sound source locations by using Fourier-based Near-field Acoustical Holography (NAH), a large number of microphone measurements is generally required to span the source region and ensure a sufficiently high spatial sampling rate. As a result, such measurements are costly, a fact which has discouraged the industrial application of NAH to identify sound source locations. However, recently, compressive sensing approaches have made it feasible to identify concentrated sound sources with a limited number of microphone measurements. In the present work, sound radiation from the front face of a diesel engine was measured by using one set of measurements from a 35-channel combo-array. The locations of significant noise sources were then identified by using three compressive sensing algorithms: Wideband Acoustical Holography (WBH), l1-norm minimization, and a hybrid approach which combined WBH and l1-norm minimization. The latter approach takes advantage of the l1’ norm’s ability to locate spatially distinct sources, and WBH’s ability to suppress “ghost” sources. It was found that the hybrid algorithm can localize and visualize the major noise sources over a broad range of frequencies, even though using a relatively small number of microphones. Finally, comments are made regarding sound field reconstruction differences between the algorithms.

Experimental formation of the 2D hologram of high-frequency source by a vector receiver in shallow water

The results of a high-frequency experimental formation of the 2D hologram of a moving noise source using a cylindrical small-sized vector-scalar antenna are presented. The purpose of the experiment is to test the efficiency of the interferometric method in the high-frequencydomain (1–15 kHz) for noise source localization. The experiment was carried out in a shallow water area with a water layer depth 87 m. The source localization method is based on processing of its interferogram. The 2D-FT (2D Fourier Transformation) of the interferogram is hologram of moving source. 2D hologram allows to coherently accumulate the sound intensity of the interferogram in a small area as focal spots in hologram domain. The focal spots localization in hologram domain depends upon the source range, velocity, and motion direction. The time dependences of source range, its velocity and motion direction are estimated on based of holographic signal processing. The comparative analysis of theoretical dependences and experimental data is carried out. [This study was supported by RFBR 19-29-06075, МК-4846.2022.4.]

Using Dark Fiber and Distributed Acoustic Sensing to Characterize a Geothermal System in the Imperial Valley, Southern California

AbstractThe Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low‐carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber‐optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ∼28‐km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high‐resolution two‐dimensional (2D) S wave velocity (Vs) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high Vs and low Vp/Vs ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.