Microphone Array Research Articles

Analysis of MAV Rotors Optimized for Low Noise and Aerodynamic Efficiency with Operational Constraints

The rapid growth of drone use in urban areas has prompted authorities to review airspace regulations, forcing drone manufacturers to anticipate and reduce the noise emissions during the design stage. Additionally, micro air vehicles (MAVs) are designed to be aerodynamically efficient, allowing them to fly farther, longer and safer. In this study, a steady aerodynamic code and an acoustic propagator based on the non-linear vortex lattice method (NVLM) and Farassat’s formulation-1A of the Ffowcs Williams and Hawkings (FW-H) acoustic analogy, respectively, are coupled with pymoo, a python-based optimization framework. This tool is used to perform a multi-objective (noise and aerodynamic efficiency) optimization of a 20 cm diameter two-bladed rotor under hovering conditions. From the set of optimized results, (i.e., the Pareto front), three different rotors are 3D-printed using a stereolithography (SLA) technique and tested in an anechoic room. Here, an array of far-field microphones captures the acoustic radiation and directivity of the rotor, while a balance measures the aerodynamic performance. Both the aerodynamic and aeroacoustic performance of the three different rotors, in line with what has been predicted by the numerical codes, are compared and guidelines for the design of aerodynamically and aeroacoustically efficient MAV rotors are extracted.

APC: Contactless healthy sitting posture monitoring with microphone array

The prevalence of poor sitting posture in daily work has become a growing concern among office workers and students due to the associated health problems. To address this issue, we design an acoustic sitting posture care system (termed, APC) based on a circular microphone array. Compared with classic posture recognition technologies such as visual perception and sensors, acoustic sensing naturally possesses advantages such as privacy protection and contactless capabilities. Concretely, our system leverages a customized and inaudible sound signal sent from a speaker to a user’s body, and an echo signal preprocessing method to sense the body posture. Our system comprises three modules: signal generation and collection, signal preprocessing, and posture classification. The signal generation and collection module is designed to create an appropriate signal waveform for transmitting the sound signal. We also develop a unique alignment method for received signals to implement background interference cancellation. In the signal preprocessing module, we propose a body profile extraction method based on the phase difference between received signals. In the posture classification module, we design an attention mechanism based classification network that can map the output of the previous module to different sitting posture categories. The experimental results show that our proposed method achieves an average accuracy of 98.4% for five common sitting postures. Furthermore, case studies conducted under different practical conditions have validated the robustness of our system.

Experimental Investigation of Mode-Frequency Scattering at Fan Stages

Abstract For the development of low-noise fan designs the sound generation must be reduced at the source, but also sound transmission effects through the rotor can be exploited to reduce the noise emitted to the far-field. Rotor shielding has been identified as a means of noise abatement, where rotor counter-rotating modes are blocked by the rotor and transmit poorly to the inlet. An effect that is rarely considered in this context is mode-frequency scattering at the rotor, which can circumvent the blockage effect by shifting the sound energy in frequency and mode order, typically to a rotor co-rotating mode order that transmits efficiently to the inlet. An experimental investigation is presented, where the transmission, reflection, and scattering of individually generated modes through a fan stage is measured by means of a loudspeaker array and microphone arrays, upstream and downstream. The highly resolved measured data comprise the variation of mode order, frequency, rotor speed, and aerodynamic operating conditions. In this study, the focus is on mode-frequency scattering, for which results are presented for high and low rotor speeds.

Localizing aeroacoustic sources in complex geometries: A hybrid method coupling 3D microphone array and time-reversal

Flow-induced noise is widely encountered in engineering domains, and noise source localization is the first step to understand the generation mechanisms. A large part of aeroacoustic noise measurements is performed in wind tunnels by using microphone arrays. A widespread method to identify the noise sources based on these measurements is the beamforming technique. This relies on a Green function, which ideally accounts for source type, flow, and reflecting boundaries. This function is generally not known analytically. An alternative approach is the time-reversal technique considered here. This method consists in propagating the sound field from the microphones back to focus points interpreted as sources. The back propagation can be done numerically with an acoustic propagation solver, which replaces the Green function needed in the beamforming. To date time reversal has been used to localize sound sources with flow in two-dimensions, without considering any reflecting/diffracting boundary. The objective of this work is to consider a three-dimensional situation with flow, and to include the presence of such boundaries to see if this can improve source localization. A synthetic sound source enclosed in a streamlined body is placed in a wind tunnel, and its sound field is diffracted by a nearby airfoil. A three-dimensional antenna with 768 microphones is used to measure the sound field, and time-reversal is performed by solving the three-dimensional linearized Euler equations with a discontinuous Galerkin method. The interest of taking into account the airfoil geometry for source localization is discussed, and some comparisons with the beamforming method are performed.

Room-scale Location Trace Tracking via Continuous Acoustic Waves

The increasing prevalence of smart devices spurs the development of emerging indoor localization technologies for supporting diverse personalized applications at home. Given marked drawbacks of popular chirp signal-based approaches, we aim at developing a novel device-free localization system via the continuous wave of the inaudible frequency. To achieve this goal, solutions are developed for fine-grained analyses, able to precisely locate moving human traces in the room-scale environment. In particular, a smart speaker is controlled to emit continuous waves at inaudible 20kHz , with a co-located microphone array to record their Doppler reflections for localization. We first develop solutions to remove potential noises and then propose a novel idea by slicing signals into a set of narrowband signals, each of which is likely to include at most one body segment’s reflection. Different from previous studies, which take original signals themselves as the baseband, our solutions employ the Doppler frequency of a narrowband signal to estimate the velocity first and apply it to get the accurate baseband frequency, which permits a precise phase measurement after I-Q (i.e., in-phase and quadrature) decomposition. A signal model is then developed, able to formulate the phase with body segment’s velocity, range, and angle. We next develop novel solutions to estimate the motion state in each narrowband signal, cluster the motion states for different body segments corresponding to the same person, and locate the moving traces while mitigating multi-path effects. Our system is implemented with commodity devices in room environments for performance evaluation. The experimental results exhibit that our system can conduct effective localization for up to three persons in a room, with the average errors of 7.49 cm for a single person, with 24.06 cm for two persons, with 51.15 cm for three persons.

Optimal Microphone Array Placement Design Using the Bayesian Optimization Method.

In addition to the filter coefficients, the location of the microphone array is a crucial factor in improving the overall performance of a beamformer. The optimal microphone array placement can considerably enhance speech quality. However, the optimization problem with microphone configuration variables is non-convex and highly non-linear. Heuristic algorithms that are frequently employed take a long time and have a chance of missing the optimal microphone array placement design. We extend the Bayesian optimization method to solve the microphone array configuration design problem. The proposed Bayesian optimization method does not depend on gradient and Hessian approximations and makes use of all the information available from prior evaluations. Furthermore, Gaussian process regression and acquisition functions make up the Bayesian optimization method. The objective function is given a prior probabilistic model through Gaussian process regression, which exploits this model while integrating out uncertainty. The acquisition function is adopted to decide the next placement point based upon the incumbent optimum with the posterior distribution. Numerical experiments have demonstrated that the Bayesian optimization method could find a similar or better microphone array placement compared with the hybrid descent method and computational time is significantly reduced. Our proposed method is at least four times faster than the hybrid descent method to find the optimal microphone array configuration from the numerical results.

On Improving the Noise Reduction Performance of Trailing Edge Serrations by Extension

Trailing edge serration is an effective method to reduce broadband noise generation by an airfoil. However, the noise reduction performance can be significantly reduced when there is flow misalignment at the serration. This experimental study investigates the impact of a shift in the serration position downstream of the airfoil trailing edge on the noise reduction performance, referred to in this paper as serration extension. Experiments were performed on a 100-mm-chord NACA 0012 wing model with sawtooth trailing edge serrations. The serration performance was studied at 0° and 7° flap-down configurations at various angles of attack. The serrations with three different extension lengths of 5, 10, and 15 mm were tested and compared with the baseline case without extension. The emitted noise was measured with a phased microphone array. The results show a significant reduction in broadband high-frequency noise by extension under loading conditions. Particle image velocimetry measurements of root flow along the wall-normal plane reveal diminished crossflow across the serration after extension. Furthermore, the extensions cause an up-to-25% increase in the maximum lift coefficient and improved or unaltered lift-to-drag ratios.

Time-domain sound field reconstruction using a rigid spherical microphone array.

A time-domain approach for interior spherical near-field acoustic holography is proposed to achieve the low-delay reconstruction of time-domain sound fields using a rigid spherical microphone array. This reconstruction encompasses the incident pressure field, the incident radial particle velocity field, and the total pressure field, which includes scattering. The proposed approach derives time-domain radial propagators through the inverse Fourier transform of their frequency-domain counterparts. These propagators are then applied to the array measurements to obtain the time-domain spherical harmonic coefficients of the interior sound field. Given the fact that the time-domain radial propagators possess finite-time support and exhibit significant high-frequency attenuation characteristics, they can be efficiently implemented using finite impulse response (FIR) filters. The proposed approach processes the signal sample-by-sample through these FIR filters, avoiding a series of issues associated with time-frequency transformations in frequency-domain methods. As a result, the approach offers higher accuracy and lower latency in reconstructing non-stationary sound fields compared to its frequency-domain counterpart and thus holds greater potential for real-time applications. Additionally, owing to the scattering effect of the rigid sphere, the approach avoids the impact of spherical Bessel function nulls and does not require the measurement of particle velocities, which renders the measurements cost effective.

Experimental study of the noise suppression of supersonic impinging jets with chevrons

Supersonic impinging jets may cause many adverse ground effects, including surface erosion, nonuniform surface heat transfer, lift loss, and acoustic loading. In this study, chevron nozzles are used to suppress the noise generation of supersonic impinging jets originated from a circular convergent nozzle with the jet Mach number of 1.2. An array of microphones is used to measure the far-field acoustic fields, and a schlieren system is employed to measure the near-field flow structures. Three impinging distances are considered to examine the differences between the impinging jets and the free jet, and to assess the effect of impinging distance on the noise characteristics. Two chevron nozzles with different penetration angles are designed to investigate the potentials of chevron nozzles in controlling the supersonic-impinging-jet noise. Results show that the chevron nozzles do not alter the directivity of overall sound pressure levels, but significantly reduce the amplitude at all emission angles. The discrete tones in the impinging jets are dramatically mitigated or eliminated, and the levels of broadband noise are also significantly reduced over a wide range of frequency band, regardless of the impingement distance. The influences of chevrons on the near-field flow structures are checked with the root-mean-square values and proper orthogonal decomposition of schlieren images, which provide more evidence on the noise suppression mechanism with chevrons.

Fast identification of coherent sound sources with the covariance matrix fitting method based on non-synchronous measurements

The Non-Synchronous Measurements is particularly effective at expanding the operating frequency range of a single microphone array. The completed cross-spectral matrix of the synthetic array, when combined with high-resolution imaging algorithms, can yield accurate sound source identification results. However, when matrix completion algorithms are applied to large synthetic arrays, their computational complexity increases significantly. Furthermore, existing integrations with high-resolution imaging algorithms often encounter difficulties in the presence of coherent sound sources. To address this problem, this paper introduces the accelerated gradient descent algorithm for the covariance matrix fitting by orthogonal least squares. The matrix completion model for non-synchronous measurements is initially simplified through matrix decomposition, thereby enabling the rapid completion of the cross-spectral matrix using the accelerated gradient descent algorithm. This is then followed by the application of the covariance matrix fitting by orthogonal least squares to achieve quick and precise identification of coherent sound sources employing the completed cross-spectral matrix. The performance of the algorithm is evaluated using numerical simulations and validated through loudspeaker experiments in an anechoic chamber. The results from these simulations and experiments reveal that the proposed algorithm not only improves matrix completion performance on large synthetic arrays but also accurately identifies the locations and correlation coefficients of coherent sound sources.

A novel transformer-enhanced and acoustic-based approach for wind turbine blade fault detection with integrated system implementation

Rising global wind power capacity urgently requires effective real-time turbine monitoring. Complex installations, high maintenance costs, and the occasional need for turbine shutdown hinder conventional monitoring methods. Acoustic-based techniques, while cost-efficient for health assessments, currently face challenges with detection precision and signal processing capabilities in complex acoustic environments. To overcome these challenges, this study proposes a low-cost, AI-driven acoustic-based health monitoring system framework for wind turbine blades, featuring enhanced detection accuracy and signal processing capabilities in complex sound environments. Firstly, a microphone array is employed to capture blade sounds with rich spatial attributes, while beamforming algorithms with a fixed orientation integrate prior spatial information. Furthermore, to further strengthen signal processing and fault detection capabilities, the Transformer model based on self-attention mechanisms is employed for feature extraction and fault diagnosis. An actual wind turbine blade health monitoring system is designed and developed to validate the usability of the proposed framework. Experimental results based on a scaled-down wind turbine model validate the proposed algorithm's effectiveness and practicality, presenting an effective approach in the wind turbine blade health monitoring domain.

Topology Optimization Design Method for Acoustic Imaging Array of Power Equipment.

Acoustic imaging technology has the advantages of non-contact and intuitive positioning. It is suitable for the rapid positioning of defects such as the mechanical loosening, discharge, and DC bias of power equipment. However, the existing research lacks the optimization design of microphone array topology. The acoustic frequency domain characteristics of typical power equipment are elaborately sorted out. After that, the cut-off frequencies of acoustic imaging instruments are determined, to meet the needs of the full bandwidth test requirements. Through a simulation calculation, the circular array is demonstrated to be the optimal shape. And the design parameters affect the imaging performance of the array to varying degrees, indicating that it is difficult to obtain the optimal array topology by an exhaustive method. Aimed at the complex working conditions of power equipment, a topology optimization design method of an acoustic imaging array for power equipment is proposed, and the global optimal solution of microphone array topology is obtained. Compared with the original array, the imaging performance of the improved LF and HF array is promoted by 54% and 49%, respectively. Combined with the simulation analysis and laboratory test, it is verified that the improved array can not only accurately locate the single sound source but also accurately identify the main sound source from the interference of the contiguous sound source.

Laser-Based Command Injection Attacks on Voice-Controlled Microphone Arrays

Voice-controlled (VC) systems, such as mobile phones and smart speakers, enable users to operate smart devices through voice commands. Previous works (e.g., LightCommands) show that attackers can trigger VC systems to respond to various audio commands by injecting light signals. However, LightCommands only discusses attacks on devices with a single microphone, while new devices typically use microphone arrays with sensor fusion technology for better capturing sound from different distances. By replicating LightCommands’s experiments on the new devices, we find that simply extending the light scope (just as they do) to overlap multiple microphone apertures is inadequate to wake up the device with sensor fusion. Adapting LightCommands’s approach to microphone arrays is challenging due to their requirement for multiple sound amplifiers, and each amplifier requires an independent power driver with unique settings. The number of additional devices increases with the microphone aperture count, significantly increasing the complexity of implementing and deploying the attack equipment. With a growing number of devices adopting sensor fusion to distinguish the sound location, it is essential to propose new approaches to adapting the light injection attacks to these new devices. To address these problems, we propose a lightweight microphone array laser injection solution called LCMA (Laser Commands for Microphone Array), which can use a single laser controller to manipulate multiple laser points and simultaneously target all the apertures of a microphone array and input light waves at different frequencies. Our key design is to propose a new PWM (Pulse Width Modulation) based control signal algorithm that can be implemented on a single MCU and directly control multiple lasers via different PWM output channels. Moreover, LCMA can be remotely configured via BLE (Bluetooth Low Energy). These features allow our solution to be deployed on a drone to covertly attack the targets hidden inside the building. Using LCMA, we successfully attack 29 devices. The experiment results show that LCMA is robust on the newest devices such as the iPhone 15, and the control panel of the Tesla Model Y.

Noise Control of Blunt Flat-Plate Using Slit and Dielectric Barrier Discharge Plasma

This paper investigates the combination of a slit at the blunt trailing edge of the flat plate and dielectric barrier discharge plasma to control the vortex shedding of the plate and its associated tonal noise. The noise and flow characteristics of the plate were measured using a far-field microphone array and the particle image velocimetry technique, respectively. The results show that the vortex shedding and the tonal noise can be significantly suppressed by the slit alone, with an average noise reduction of approximately 10 dB in the test Reynolds number. In addition, installing a plasma actuator inside the slit further suppresses the vortex shedding and reduces tonal noise. However, the additional control efficiency of the plasma decreases with increasing wind speeds, with a further 8 dB reduction at a wind speed of U∞=10 m/s (corresponding to an inducing blowing rate BR of 4.5%). However, only an additional 1.5 dB noise reduction is achieved at U∞=20 m/s (BR=2.25%). The particle image velocimetry snapshots were analyzed by proper orthogonal decomposition. The measurements clearly show the variation in vortex shedding at the trailing edge of the plate, revealing the underlying flow mechanisms that lead to the observed noise variations and frequency changes.

Realization of adaptive beamformer on open-source hardware

Realization of an efficient system for extracting useful audio signals in the presence of interferences is an important engineering problem in the field of acoustics. This paper proposes a method for extracting sound signals from a specific direction of incidence. A microphone array consisting of eight microphones was used, coupled with space-time signal processing executed in real time on hardware. The microphone signals are filtered by an adaptive beamformer, whose coefficients are optimized in real time on open-source hardware using the Least Mean Square algorithm. This paper describes the characteristics and limitations of the used microphone array. Testing the system through simulation indicates that extracting narrowband and wideband signals using the presented adaptive beamforming method is theoretically possible. This paper aims to experimentally evaluate the algorithm under real-world conditions, as well as identify the limitations of extracting wideband signals. Adaptation of the filter coefficients and filtering the signals from the microphones was implemented on Bela hardware, specialized for processing audio signals. This experiment highlights the limitations that arise from extracting a wideband signal using this type of hardware in real conditions. By comparing the useful and filtered signals in both time and frequency domains, the quality of the filtering was analyzed. Our experiments suggest that the current hardware specifications are a limiting factor for successful wideband signal filtering in real conditions, as they limit the maximum possible order of the adaptive filter, which proved to be insufficient.

Room Impulse Response Dataset of a Recording Studio with Variable Wall Paneling Measured Using a 32-Channel Spherical Microphone Array and a B-Format Microphone Array

This paper introduces RSoANU, a dataset of real multichannel room impulse responses (RIRs) obtained in a recording studio. Compared to the current publicly available datasets, RSoANU distinguishes itself by featuring RIRs captured using both a 32-channel spherical microphone array (mh acoustics em32 Eigenmike) and a B-format soundfield microphone array (Rode NT-SF1). The studio incorporates variable wall panels in felt and wood options, with measurements conducted for two configurations: all panels set to wood or felt. Three source positions that emulate typical performance locations were considered. RIRs were collected over a planar receiver grid spanning the room, with the microphone array centered at a height of 1.7 m. The paper includes an analysis of acoustic parameters derived from the dataset, revealing notable distinctions between felt and wood panel environments. Felt panels exhibit faster decay, higher clarity, and superior definition in mid-to-high frequencies. The analysis across the receiver grid emphasizes the impact of room geometry and source–receiver positions on reverberation time and clarity. The study also notes spatial variations in parameters obtained from the two microphone arrays, suggesting potential for future research into their specific capabilities for room acoustic characterization.

Comparison of conventional and adaptive acoustic beamforming algorithms using a tetrahedral microphone array in noisy environments

In situ acoustic measurements are often plagued by interfering sound sources that occur within the measurement environment. Both adaptive and conventional beamforming algorithms, when applied to the outputs of a microphone array arranged in a tetrahedral geometry, are able to capture sound sources in desired directions and reject sound from unwanted directions. Adaptive algorithms may be able to measure a desired sound source with greater spatial precision, but require more calculations and, therefore, computational power. A conventional frequency-domain phase-shift algorithm and a modified adaptive frequency-domain Minimum Variance Distortionless Response (MVDR) algorithm were applied to simulated and recorded signals from a tetrahedral array of omnidirectional microphones. The algorithms are described mathematically and demonstrated on both deterministic and real-world sound data, to quantitatively validate and compare their performance and to provide listening examples of their outputs in a variety of acoustically replicated environments. [Work supported by Portland State University.]

Robust 3D localization of anomalies in reverberation time measurements using the sound field scanning method

Reverberation time measurements form the basis for room acoustic optimizations of existing building structures. During the verification of the achieved room acoustic improvements, anomalies may appear in the reverberation time signal which may be hard to spatially localize, especially in spaces with demanding acoustic requirements such as large, open workspaces, or concert halls. This contribution focuses on the application of the Sound Field Scanning technology to the fast spatial localization of room reflections. In this process, an omnidirectional sound source is positioned at an observation point in the room and periodically excited with band-limited pulses. At the same observation point, an acoustic camera system consisting of a rotating linear microphone array is oriented towards the preferred spatial direction. The emitted pulses and associated room reflections are captured on the measurement surface of the rotating microphone array. Acoustic images with high depth resolution are generated in parallel planes to the measurement surface. In complex situations, the task of spatially localizing anomalies in the reverberation time signal can be reduced to a few measurements from different viewing angles, thus, significantly accelerating the problem-solving process with high confidence. The method is exemplarily described through the room acoustic analysis of a University Lecture Hall.

Simulation of acoustical parameters of churches in a virtual acoustics laboratory

Current ISO standards for acoustical assessment limit the use of traditional mono-dimensional microphones for measuring equipment. However, microphone arrays offer more accurate spatial information compared to traditional microphones. This presents an opportunity to enhance research on architectural acoustics and preserve the acoustics of cultural heritage more effectively. Furthermore, modern recording studios equipped with virtual acoustics systems allow for the integration of spatial room impulse responses. This enables real-time auralization in controlled environments and enhances the overall immersive audio experience for users and musicians. This paper analyzes the main acoustical parameters obtained from spatial impulse responses captured in churches using various ambisonic microphones and inserted into a controlled, interactive, and immersive virtual acoustics system. The captured spatial acoustic measurements are then reproduced and evaluated in a virtual acoustics laboratory to identify any discrepancies between real and virtual spaces.

Validation of auralized impulse responses considering masking, loudness and background noise

The use of outdoor virtual scenarios promises to have a lot of potential to facilitate reproducible sensory evaluation experiments in laboratory. Auralizations allow for the integration of simulated or measured sound sources and transfer paths between the sources and receivers. Nonetheless, pure simulations can lack perfect plausibility. This contribution investigates the augmentation of auralized outdoor scenes based on simulated impulse responses (IRs) by ambient or background sounds. For this purpose, foreground events such as car pass-bys are created by simplified simulation of impulse responses. Due to their large number of events, however, ambient sounds are typically not simulated. Instead, spherical microphone array recordings can be used to capture the background sound. Using synthesized car sounds, we examine how much the augmentation by background sound improves the auditory plausibility of simulated impulse responses in comparison with the equivalent measured ones.