Acoustic Source Research Articles

Optimization of an active device for global control of low-frequency wall reflections in a semi-anechoic room

An active device has been designed and built at LMA to control low-frequency reflections on the absorbing walls of a semi-anechoic room: the sound pressure reflected by the walls in the presence of an unknown source is estimated by linear filtering of the total sound pressure near the walls, then neutralized using acoustic sources placed on the walls. Here, we present 2D numerical simulations, involving monopole sources and series of damped analytic modes, which have enabled us to optimize the active device, in particular to (i) deal with resonance frequencies at which cancelling the diffracted pressure near the walls is not sufficient to cancel it inside the room, (ii) minimize the number of the total pressure measurement points required to estimate the pressure diffracted by the walls at each location, and (iii) select the strategy for minimizing the virtual signals corresponding to the diffracted pressure. Simulations show that with the optimized device, the control remains efficient up to frequencies corresponding to one wall source per wavelength and a little less than two pressure sensors per wavelength. Experiments are underway to compare measurements with simulations.

ATD-300 an AI empowered miniature acoustic device for automatic gunshot attacks detection and image capture

Built on over 30 years of acoustic source recognition expertise in transient impulsives signature, recently highly empowered by neural networks, and wave propagation model driven algorithms, ACOEM has developed the ATD-300, an acoustic sensor for automatic gunshot detection, identification and localization. What sets this sensor apart from the competition is its reliability in terms of detection rate over false alarm and robust high resolution shooter pointing capability. Therefore it can be used directly by police departments without third-party human validation. Resulting from the design effort to distribute intelligence among a collaborative sensor network, processing and artificial intelligence algorithms are fully embedded locally, enabling an alert to be raised in less than three seconds and a camera to be pointed at the shooter with only one sensor. In addition, as the system is already installed in several American cities, we will show how a device-to-server distributed artificial intelligence approach continuously improves the performance of the solution, fed by real field data.

Systematic analysis of acoustic source localization maps for performance assessment

Noise pollution is a raising problematic mainly associated to the development of industry, cities, and transportation. In that context, the characterization of noise sources is key point to help the understanding of noise generation mechanisms and to be able to develop effective noise reduction strategies. Microphones phased array measurements can be used as input to solve the inverse problem of source localization allowing to obtain source maps for each frequency of interest. Conventional beamforming (CBF) is the most famous source localization algorithm which uses the interpretation of the propagation delays measured between each array microphones. However, the analysis of output source maps can be made difficult by the low spatial resolution in the low-frequency range and the presence of side-lobes associated with microphones distribution that can lead to additional wrong sources. This paper presents a systematic analysis of source maps to identify potential noise sources by using different methods (local maxima, Metropolis-Hastings). The set of potential noise sources can then be compared to the set of real sources to assess the CBF performances. This methodology is successfully applied to measurements performed in anechoic room for various source configurations highlighting CBF limitations (spatial resolution, correlated sources, reflective environment).

A numerical model calibrated by in-situ measurement for predicting the underwater radiated noise of an azimuth thruster structure of a passenger ship

In a global context of limiting the impact of noise pollution on the behavior of marine fauna, the understanding of acoustic radiation phenomena from underwater sound sources of a passenger ship is of primary importance. Although diesel engines and propellers are considered to be ones of the main sources of ship noise, our observations have shown that immersed motors contribute significantly to the noise radiated into the water by passenger ships at low speeds. This contribution summarizes a semi-empirical method for estimating the noise radiated into the water from an azimuth thruster-type structure. An analysis of the vibroacoustic behavior in water of the structure excited by an internal acoustic source is detailed. Beyond the complexity of performing full-scale measurements in a noisy environment, the analysis of the measurements allows to estimate the vibration modes of the immersed structure. A numerical model of the dedicated structure, calibrated on the basis of an experimental modal analysis, is used to estimate the pressure field radiated by the structure into the water. As a result of these analyses, a simplified model of radiated noise in the water is developed for use in nominal thruster operation.

Cascaded Thermoacoustic amplifier

In this study, we explore the amplification of an incident acoustic wave using the thermoacoustic effect and its applicability for low-temperature energy harvesting. The thermoacoustic effect can be exploited to develop thermoacoustic engines, whose potential for thermal energy harvesting has been extensively studied. In their simplest form, they consist of a porous material inserted in a waveguide, in which a temperature difference is applied and leads to the generation of a thermoacoustic instability. Here, we propose the theoretical and experimental study of an alternative system to the conventional thermoacoustic engine. The system considered here differs from the typical engine in that it exhibits no self-excited instabilities, but only relies on the amplification of an acoustic wave. The experimental set-up consists of a cascaded network of heated porous materials, coupled to an acoustic source and an alternator. This device allows to control several parameters, such as the operating frequency and input power, and it can be designed to achieve a high amplification ratio. Our work offers a new perspective on energy harvesting using the thermoacoustic effect.

Aeroacoustic modeling of a low Reynolds number rotor in the wake of a cylindrical beam

In micro air vehicles, low Reynolds number rotors operating in close proximity to the fuselage raises the question of interaction noise as a prominent acoustic source. This paper proposes to comprehensively explore the interaction noise generation mechanisms, employing numerical simulations, experimental approaches, and analytical modelling. The focus is on scenarios where a low Reynolds number rotor is located in the wake of a cylindrical beam, and oppositely when the beam is in the wake of the rotor. In both scenarios, it is observed experimentally that the amplitudes of the BPF harmonics are increased with respect to that obtained without beam. This increase is higher when the rotor is in the wake of the beam compared to when the beam is in the wake of the rotor. The numerical simulation is shown to reproduce quite well the envelope of the amplitudes of the BPF harmonics obtained experimentally in both scenarios. Interestingly, by applying Ffowcs-Williams and Hawkings analogy on elementary surfaces, and not on the whole rotor-beam surface, the main sound generation mechanism was found to be the unsteady loading on the beam in both scenarios. Finally, an analytical modeling of the noise source mechanism is compared with experimental and numerical results.

Numerical simulation of the flow-induced noise of a ducted diaphragm using the Lattice Boltzmann Method

Acoustic discretion is of prime importance for submarines while operating, in order not to be detected. One of the submarine acoustic sources is the noise induced by water flows passing through singularities in pipes ending at the hull, thus radiating acoustic waves in the vessel surroundings. Predicting the noise induced by singularities in pipes is then fundamental to determine the acoustic signature of an underwater ship. Several Computational Aero-Acoustics methods have been implemented in order to predict the sound induced by singularities such as diaphragms and perforated plates. In this study, the Lattice Boltzmann Method (LBM) coupled to Large Eddy Simulation (LES) is used to simulate the flow passing through a diaphragm and to predict the induced noise. The method is first implemented for an airflow in a rectangular duct, with the final objective of being applied to confined water flows encountered in circular or rectangular ducts.

Hybrid acoustic modeling: far-field predictions from scanning 3D sound intensity data

This research introduces a novel methodology for predicting the far-field acoustic behavior of complex vibro-acoustic sources, utilizing 3D sound intensity data acquired through Scan&Paint 3D's continuous scanning technology. By combining this experimental dataset with the computational modeling capabilities of the commercial acoustic package Actran, we establish a hybrid method capable of accurately computing noise generated by intricate vibro-acoustic phenomena. The use of a 3D sound intensity probe, in combination with an infrared stereo camera, accelerates the acquisition of acoustic data across an extensive area. This approach not only delivers detailed insights into the source's near-field acoustic behavior but also provides inputs for the computational model, allowing us to model how the vibrating structure radiates. Extensive validation is performed by calculating prediction errors across multiple observation points, ensuring high quality far-field predictions. The integration of extensive experimental data with advanced computational modeling marks a significant leap forward in evaluating the far-field impact of complex acoustic sources. This allows the industrial user to assess the performance of multiple potential mitigation solutions through simulation, quickly, easily, and reliably.

Methodology for 3D sound synthesis of directional acoustic sources by higher-order ambisonics

This paper presents the 3D sound field synthesis using both the multimodal method and higher-order ambisonics (HOA) of the pressure field radiated by directional acoustic sources. Ambisonics is a technique for encoding and reproducing measured or modeled (virtual) sound pressure field, based on a decomposition of the acoustic field over spherical harmonics. The directional source considered in this work is an acoustic horn excited by a flat piston. The free-field radiation from this horn is first modeled accurately over a wide frequency range using the multimodal method, which requires relatively low computational resources. This radiated pressure field, collected on a dual-layer sphere of virtual sensors distributed over a Lebedev geometry, allows its projection into the ambisonic domain. The pressure field is then synthetized in the laboratory's 3D 5th order HOA spatialization sphere, which consists of fifty-six loudspeakers. This offers the ability of listening to the radiated sound using a higher-order ambisonic synthesis of a 'virtual' source before it is manufactured. To qualitatively evaluate the performance of the proposed procedure, the transfer function of the synthesized horn is measured around the listening point within the spatialization sphere. Key words : 3D sound synthesis, high-order ambisonics, directive sources, waveguides, horn, multimodal method

Pertinence of finite element method for impulse localization in urban environments

Although urban combat is nothing new, recent conflicts have shed light on Western armies' difficulties when operating in such environments. Thus, new surveillance and hazard detection challenges in complex environments are addressed. A new decision aid tool for acoustic sensor positioning has been developed to improve reconnaissance performance. The software's sensor location optimization kernel is based on a genetic algorithm developed by our partners from FKIE. It resolves successive localization problems using pre-computed Times Of Arrival (TOA) between an impulsive acoustic source and various surveillance microphones. The present study discusses the pertinence of the Time-Domain Finite-Element Method (TD-FEM) to simulate wave propagation within an urban area to obtain TOA and resolve localization problems. The approach is compared to experimental measurements in an urban area, and the pros and cons of the TD-FEM for this configuration are discussed.

Assessment of planar array accuracy for 3D sound source reconstruction with Bayesian Focusing

As planar microphone arrays were initially designed for bidimensional sound source localisation, their use for three-dimensional acoustic imaging consistently suffers from a poor resolution along the normal axis. Such a statement is already well documented for beamforming approaches and their declensions. Bearing this in mind, this paper delves into the possibilities offered by inverse methods and especially iterative Bayesian Focusing to tackle this issue and deliver accurate source positions in three dimensions based on planar array measurements only. To this end, an experimental set up is designed: omnidirectional sources are mounted in a wooden mock-up featuring faces at different distances from an 81 MEMs planar array. Based on this measurements, a benchmark study of sound source reconstruction on a 3D mesh of the mock-up is conducted and compared to classical 2D acoustic maps set at different depths. The latter process is declined for various source correlation values and at extended frequency ranges. By doing so, the current paper delivers an overview of the ability to discriminate acoustic sources along the normal axis of a planar array, on a simple and well controlled test case, with a view to provide guidelines for further applications of 3D acoustic imaging on complex geometries.

A signal processing system for infrasound-based detection and tracking of tornadoes

It has been established that tornadic storms emit infrasound at infrasonic frequencies and that this sound can be detected from practically significant distances exceeding 100 km in some cases. This work describes a signal processing system that is used to ingest data from a network of infrasound arrays and produce near real-time detections and ground tracks of multiple, simultaneously active tornadic storms. Specifically, a brief review of a particular array network and corresponding hardware is presented followed by detailed descriptions of the array signal processing architecture and source geolocation system. Emphasis is placed on algorithms for multiple moving source acoustic source bearing tracking, low SNR signal detection, mitigation of errors created by anomalous acoustic events, and multiple-array data association. Performance results corresponding to simulated and recorded data are presented.

Acoustic detection of Unmanned Aerial Vehicles in flight with respect to the signal-to-noise ratio using machine learning

Nowadays, unmanned Aerial vehicles (UAV) are more and more commonly found in the world for a variety of activities. It has become an important task to detect and classify them in order to manage their potential malicious intentions. Current detection and classification methods mostly rely on feature extraction and the use of artificial neural networks that can be heavily impacted by the signal-to-noise ratio (SNR). The approach proposed aims to solve a two-class problem (presence or absence of an UAV) by extracting information on the content of the acoustic source, and then presenting it as input to a neural network. The features used are strongly inspired by the harmonic sound emitted by UAV. Attention is also given on the SNR of the scene. Indeed, various disturbing sources such as trains, helicopters or footsteps are involved from an open library. These signals are added to our recordings of UAVs in flight by tuning their amplitude to obtain different SNRs. The aim is to establish the performance of the detection system as a function of the SNR of the scene.

Impact of Model Knowledge on Acoustic Emission Source Localization Accuracy

Reliable and precise damage localization in mechanical structures is of high importance in the context of structural health monitoring (SHM). The acoustic emission (AE) method has already shown its excellent suitability for damage localization. However, low signal-to-noise ratios (SNRs) are often prevalent in SHM, thus an increase in localization accuracy and robustness is still in demand. The present study faces this task through the integration of various model knowledge for AE source localization. The basis of the presented algorithm is the consideration of the dispersive behavior of elastic waves in thin-walled structures. The continuous wavelet transform (CWT) is used to obtain time-frequency representations of the signals, where frequency-dependent values for time-of-arrival (TOA) are extracted. Furthermore, the algorithm incorporates the knowledge that all sensors receive signals with the same time and location of origin, as well as the slightly different sensitivity of the theoretically equal sensors. The final localization results are achieved by a two parameter grid search optimization. The algorithm is experimentally tested on a large aluminum plate with four piezoelectric wafer active sensors (PWASs) arranged in an array of 100 mm × 100 mm. The mean localization error of pencil lead breaks at ten different positions within the sensor array is used as an accuracy measure. It is shown that as more of the described model knowledge is incorporated into the localization, the accuracy increases. With the final algorithm, the mean localization error is more than halved compared to AE localization based on classical TOA estimation. Although the experiment described is conducted under laboratory conditions, the remarkable increase in accuracy suggests that AE source localization may be successful even at low SNR as typical for operational conditions.

Numerical simulation study of acoustic source characteristics of liquid level monitor based on infrasound waves

Abstract To investigate the sound source characteristics of infrasound waves generated during the operation of the gas explosion liquid level monitoring instrument, with a focus on the aerodynamic noise produced by the monitoring device, a mixed numerical method was used to simulate and study the impact of different nozzle diameters, gas explosion pressures, and casing pressures on the instrument’s infrasound frequency range. The results indicate that gas explosion pressure, casing pressure, and nozzle diameter primarily affect the spectral characteristics within the 10 Hz to 20 Hz range. As the gas explosion pressure and nozzle diameter increase, the sound pressure level in the internal sound field also increases, and the peak frequency shifts higher. Conversely, with an increase in casing pressure, the sound pressure level in the internal sound field decreases, and the peak frequency shifts lower. The research findings can provide a theoretical basis for the development of the instrument.

Azimuthally-distributed wavy inner wall treatment for high subsonic jet noise control

The noise generated by subsonic jet nozzles, commonly encountered in civilian aircraft, is rather significant and propagates in both the upstream and downstream directions due to large-scale and fine-scale turbulence structures. In this paper, a distinctive inner wall treatment strategy, denoted as the Azimuthally-distributed Wavy Inner Wall (AWIW), is proposed, which is aimed at mitigating jet noise. Within this strategy, a circumferentially dispersed treatment wall characterized by a minute wavy pattern is substituted for the smooth inner wall in proximity to the nozzle outlet. To assess the effectiveness of the AWIW treatment, we conducted numerical simulations. The unsteady flow field and far-field noise were predicted by employing Large Eddy Simulations (LES) coupled with the Ffowcs Williams and Hawkings (FW-H) integration method. To gain a comprehensive understanding of the mechanism underlying the noise reduction facilitated by the AWIW treatment, it examined physical parameters such as the Lighthill source acoustic source term, the turbulent kinetic energy acoustic source term, and the shear layer instability. The results reveal that the AWIW treatment expedites the instability within the shear layer of the jet, leading to an early disruption of the jet shear layer, and consequently turbulent structures in varying sizes are generated downstream. This process effectively regulates the generation and emission of jet noise. By controlling the minor scale turbulence through the AWIW treatment, the mid- and high-frequency noise within the distant field can be significantly reduced. In the context of the flow field, the introduction of AWIW also leads to a decrease in drag on the inner wall surface of the jet, thereby improving the overall aerodynamic performance of the nozzle. Considering these attributes, the AWIW strategy emerges as a viable technique for the reduction of jet noise.

High-resolution observations of shallow-water acoustic propagation with distributed acoustic sensing.

Distributed acoustic sensing (DAS), converting fiber-optic cables into dense acoustic sensors, is a promising technology that offers a cost-effective and scalable solution for long-term, high-resolution studies in ocean acoustics. In this paper, the telecommunication cable of Martha's Vineyard Coastal Observatory (MVCO) is used to explore the feasibility of cable localization and shallow-water sound propagation with a mobile acoustic source. The MVCO DAS array records coherent, high-quality acoustic signals in the frequency band of 105-160 Hz, and a two-step inversion method is used to improve the location accuracy of DAS channels, reducing the location uncertainty to ∼2 m. The DAS array with refined channel positions enables the high-resolution observation of acoustic modal interference. Numerical simulations that reproduce the observed interference pattern suggest a compressional speed of 1750 m/s in the sediment, which is consistent with previous in situ geoacoustic measurements. These findings demonstrate the long-term potential of DAS for high-resolution ocean acoustic studies.

A Hybrid GAN-Inception Deep Learning Approach for Enhanced Coordinate-Based Acoustic Emission Source Localization

In this paper, we propose a novel approach to coordinate-based acoustic emission (AE) source localization to address the challenges of limited and imbalanced datasets from fiber-optic AE sensors used for structural health monitoring (SHM). We have developed a hybrid deep learning model combining four generative adversarial network (GAN) variants for data augmentation with an adapted inception neural network for regression-based prediction. The experimental setup features a single fiber-optic AE sensor based on a tightly coiled fiber-optic Fabry-Perot interferometer formed by two identical fiber Bragg gratings. AE signals were generated using the Hsu-Nielsen pencil lead break test on a grid-marked thin aluminum plate with 35 distinct locations, simulating real-world structural monitoring conditions in bounded isotropic plate-like structures. It is demonstrated that the single-sensor configuration can achieve precise localization, avoiding the need for a multiple sensor array. The GAN-based signal augmentation expanded the dataset from 900 to 4500 samples, with the Wasserstein distance between the original and synthetic datasets decreasing by 83% after 2000 training epochs, demonstrating the high fidelity of the synthetic data. Among the GAN variants, the standard GAN architecture proved the most effective, outperforming other variants in this specific application. The hybrid model exhibits superior performance compared to non-augmented deep learning approaches, with the median error distribution comparisons revealing a significant 50% reduction in prediction errors, accompanied by substantially improved consistency across various AE source locations. Overall, this developed hybrid approach offers a promising solution for enhancing AE-based SHM in complex infrastructures, improving damage detection accuracy and reliability for more efficient predictive maintenance strategies.

Embodied/Encoded: A Study of Presence in Digital Music

Presence in Embodied/Encoded is concerned with the physical and embodied dimensions of musicking in relation to digital-informational representations of such phenomena. I explore presence through practices of recording, creative coding, audio production, and spatial electronic music composition. Of particular interest is the link between presence and the sensual/corporeal aspects of sound production and listening. Research in embodied music cognition and extended reality provide a foundation for this type of meaning formation. In the context of immersive electronic music, I suggest that physical presence – a sense of ‘being somewhere’—emerges not just from images/representations of place, but from peripheral aspects of the (embodied) acoustic experience such as spatial proximity and distance, diffuseness, resonance and reverberation, noise floor, etc. Consequently, musical meaning in “Embodied/Encoded” moves away from the symbolic dimension of electronic sounds toward meaning as an outcome of embodied interaction with the environment. The concept of presence can also apply to ‘mixed’ music, or combinations of acoustic and electronic sources, in which virtual presence is complicated by real bodies and spaces. Digital technology renders sound a flexible, malleable entity—a ‘flickering’ signifier to borrow from Hayles—capable of reconfiguring presence in creative ways. The dance between encoded and embodied dimensions inspires and informs this artistic research. Through a body of immersive music and multimedia documentation, I unpack connections between presence and its digital abstractions.

Analysis of Thermo-Acoustic Instabilities Induced by Hydrogen Swirling Flames

Abstract A considerable research effort has been concerned combustion dynamics of systems fed with hydrocarbon fuels. The case of pure hydrogen/air flames deserves to be specifically considered because hydrogen is highly reactive, has a tendency to develop thermo-diffusive instabilities, is envisaged in many future applications, most notably in gas turbines, and is less well documented. Thermo-acoustic instabilities of pure hydrogen flames are here investigated in a configuration where hydrogen is injected in-crossflow in a swirling stream of air. The study is focused on operating conditions that lead to oscillatory regimes. Using Abel-transformed phase-averaged images of OH* emission and visible light emission in burnt gases, it is shown that the OH* signal evolves approximately in phase with the heat release rate. This signal is then used to determine the local Rayleigh source term that feeds acoustic energy in the oscillation. The contributions of this term are examined using a space–time analysis based on an integration of the source term in the transverse direction. This procedure allows a detailed analysis of the processes that contribute to the acoustic energy in the system, showing, in particular, that a strong positive addition of acoustic energy results from a roll-up of the flame tip and from the quick cyclic back propagation of the flame to the injector tip. A global integration of the Rayleigh source term is then used together with a volume-integrated acoustic energy to estimate the growth rate associated with these driving processes and estimate the damping rate. A special experimental method is then exploited to determine the effective growth rate of the instability. The system allowing a sweep in frequency, self-sustained instabilities obtained at different frequencies are used to extract the specific instability frequency band of the burner. Finally, the flame is externally forced in order to measure its flame-describing function.