A hybrid deconvolution approach to separate static and moving single-tone acoustic sources by phased microphone array measurements

Microphone arrays are commonly used for noise source localization and power estimation in aeroacoustic measurements. The delay-and-sum (DAS) beamformer, which is the most widely used beamforming algorithm in practice, suffers from low resolution and high sidelobe level problems. Therefore, deconvolution approaches, such as the deconvolution approach for the mapping of acoustic sources (DAMAS), are often used for extracting the actual source powers from the contaminated DAS results. However, most deconvolution approaches assume that the sources are uncorrelated. Although deconvolution algorithms that can deal with correlated sources, such as DAMAS for correlated sources, do exist, these algorithms are computationally impractical even for small scanning grid sizes. This paper presents a covariance fitting approach for the mapping of acoustic correlated sources (MACS), which can work with uncorrelated, partially correlated or even coherent sources with a reasonably low computational complexity. MACS minimizes a quadratic cost function in a cyclic manner by making use of convex optimization and sparsity, and is guaranteed to converge at least locally. Simulations and experimental data acquired at the University of Florida Aeroacoustic Flow Facility with a 63-element logarithmic spiral microphone array in the absence of flow are used to demonstrate the performance of MACS.

A deconvolution approach for the mapping of acoustic sources (DAMAS) determined from phased microphone arrays

Inlet fan noise in turbofan engines is frequently characterized in terms of modal amplitude distribution. The modes can be measured nonintrusively using an array of wall mounted microphones. At high frequency, the number of cuton modes can be much larger than any reasonable number of microphones. This suggests a beamforming analysis technique, rather than a least squares fit, as an appropriate method to extract the mode amplitude from the data. The quality of beamforming output is limited by array resolution and sidelobes. The CLEAN deconvolution algorithm has been used in the past to attempt to improve mode maps from beamforming processing. The recently introduced DAMAS algorithm is a much more comprehensive deconvolution technique, and is well suited to processing mode maps. The benefit of DAMAS is illustrated using simulated mode data. The engine inlet is represented as a cylinder with uniform flow. Two array designs are considered. In each case, several mode distributions are postulated and used to create synthetic array data. Beamforming is applied to create mode maps, and DAMAS is used to deconvolve the array response functions from the mode maps. The results are evaluated by comparing the true mode distributions, the beamform maps, and the deconvolved maps.

Beamforming algorithms have been applied in multiple contexts in aeroacoustic applications, but difficulty arises when applying these to the partially correlated and distributed sources found in jet noise. To measure and more accurately distinguish correlated sources, cross-beamforming methods are employed to incorporate correlation information. Deconvolution methods such as DAMAS-C, an extension of the deconvolution approach for the mapping of acoustic sources (DAMAS), remove array effects from cross-beamforming applications and further resolve beamforming results. While DAMAS-C results provide insight to correlation between sources, the extent to which these results relate to source correlation remains to be analyzed. Numerical simulations of sources with varying degrees of correlation are provided to benchmark the DAMAS-C results. Finally, correlation lengths are established for DAMAS-C results from measurements for full-scale military jet noise sources. [Work supported by ONR.]

Aeroacoustic measurements in closed-section wind tunnels often employ phased microphone arrays that are mounted flush to the wall of the test section. Phased arrays can measure the directivity of multiple acoustic sources within a sound field across all frequencies, but require dozens of microphones in typical applications. Furthermore, the turbulent boundary layer developed by wind tunnels engulf the phased arrays in loud pressure fluctuations that drown out the acoustics trying to be measured. This paper describes an alternative approach for measuring the directivity of a single broadband acoustic source that significantly reduces the number of microphones needed. This approach was developed from experimental testing of an acoustic metamaterial-based pressure sensing array in Virginia Tech’s Anechoic Wall Jet Tunnel. The measurements obtained reveal that an acoustic metamaterial-based array can be designed to passively reinforce select pressure waves as a function of frequency and the acoustic source’s location.

Imaging of aeroacoustic noise sources is routinely accomplished with geometrically fixed phased arrays of microphones. Several decades of research have gone into improvement and optimization of sensor layouts, selection of basis models, and deconvolution algorithms to produce sharper and more localized images of sound-producing regions in space. This paper explores an extension to conventional phased array measurements that uses slowly, continuously moving microphone arrays with and without coupling to rigid fixed arrays to improve image quality and better describe noise mechanisms on turbofan engine sources such as jet exhausts and turbomachinery components. Three approaches are compared in the paper: fixed receiver beamforming (FRBF), continuous-scan beamforming (CSBF), and multireference CSBF (MRCSBF). The third takes advantage of transfer function matrices formed between fixed and moving sensors to achieve effective virtual arrays with spatial density one to two orders of magnitude higher, with practical sensor budgets and scan speeds. The MRCSBF technique produces array sidelobe rejection that approaches the theoretical array pattern of a continuous two-dimensional (2D) aperture. The implications of this finding are that better source localization may be achieved with conventional delay and sum (DAS) beamforming (BF) with practical sensor budgets, and that an improved starting image of the sound source can be provided to deconvolution algorithms. These findings are demonstrated on analytical and experimental examples from a low-cost rotating phased array using point sound sources, as well as linear scanning array experiments of an impinging jets point source and a near-sonic jet nozzle exhaust.

Identifying equivalent sound sources from aeroacoustic simulations using a numerical phased array

Near-field measurements have many advantages over the conventional far-field measurements in the phased array measurements. Source construction is an improved measurement technique with the test range between near-field and far-field measurement. Probe correction have been generally studied in all near-field scanning methods. Yet, probe calibrations techniques are not discussed for phased array measurements. In this paper, probe calibrations techniques for phase array measurements will be presented. With probe corrected calibration, the phased array and the probes are not treated as phase-center points, and higher measurement accuracy is achieved.

We present a method to map the spectral and spatial distributions of radioactive sources using a limited number of detectors. Locating and identifying radioactive materials is important for border monitoring, in accounting for special nuclear material in processing facilities, and in cleanup operations following a radioactive material spill. Most methods to analyze these types of problems make restrictive assumptions about the distribution of the source. In contrast, the source mapping method presented here allows an arbitrary three-dimensional distribution in space and a gamma peak distribution in energy. To apply the method, the problem is cast as an inverse problem where the system’s geometry and material composition are known and fixed, while the radiation source distribution is sought. A probabilistic Bayesian approach is used to solve the resulting inverse problem since the system of equations is ill-posed. The posterior is maximized with a Newton optimization method. The probabilistic approach also provides estimates of the confidence in the final source map prediction. A set of adjoint, discrete ordinates flux solutions, obtained in this work by the Denovo code, is required to efficiently compute detector responses from a candidate source distribution. These adjoint fluxes form the linear mapping from the state space to the response space. The test of the method’s success is simultaneously locating a set of 137Cs and 60Co gamma sources in a room. This test problem is solved using experimental measurements that we collected for this purpose. Because of the weak sources available for use in the experiment, some of the expected photopeaks were not distinguishable from the Compton continuum. However, by supplanting 14 flawed measurements (out of a total of 69) with synthetic responses computed by MCNP, the proof-of-principle source mapping was successful. The locations of the sources were predicted within 25 cm for two of the sources and 90 cm for the third, in a room with an ˜4-× 4-m floor plan. The predicted source intensities were within a factor of ten of their true value.

Human activities in the marine environment coupled with the efficient propagation of acoustic waves, have significantly increased ocean noise levels. This rise poses a threat to marine biodiversity, especially impacting vocal-dependent marine mammals. Therefore, obtaining a more comprehensive understanding of the complex ocean soundscape, shaped by both natural and anthropogenic sources, is essential.Ocean-bottom seismometer (OBS) datasets present an opportunity to explore the marine acoustic noise field. OBS hydrophones can be used to effectively study regional marine soundscapes. Additionally, the three-component OBS seismometers capture acoustic-to-seismic conversions from the water column, enabling the detection and localization of acoustic events.Through the analysis of OBS hydrophone recordings from the NE Atlantic offshore Ireland, we develop a frequency-dependent empirical sound propagation model for the area. The model provides information on (1) the spectral amplitude decay of sound sources in the region and (2) the distance between OBSs and acoustic sources.To construct the model, we consider ship noise from individual vessels recorded by OBSs at known distances from the source, using Automatic Identification System (AIS) ship-tracking data. As a ship moves away from its closest point of approach (CPA) to an OBS, the hydrophone records the evolution of the frequency-dependent ship's acoustic signal spectral amplitude with distance. This enables us to compute amplitude decay curves for narrow frequency bands from different vessel signals recorded at various OBSs. We apply a signal-to-noise ratio (SNR) quality control criterion and consider ships sailing along 'straight' paths at a constant speed (< 2 kn variation). After normalizing and scaling the CPAs of the different curves to a reference, we stack them for each frequency band and compute polynomial fits for the stacked amplitude decay curves. We analyse the number of vessel tracks needed to build a reliable empirical model. Numerical simulations are computed to further understand the acoustic propagation properties from our empirical model.The goal is to investigate (1) how spectral amplitudes at different frequencies behave with distance from the sound sources, (2) the efficiency of frequency-dependent sound propagation in the ocean in regions with variable seafloor morphologies, and (3) the potential use of the empirical model to obtain distances to other sound sources with unknown locations, such as Baleen whales. To achieve this, we compute ratios of spectral amplitudes for pairs of different frequency bands using the fitted amplitude decay curves. We test the model's ability to locate other vessels with known AIS positions before using it to locate different sound sources with unknown positions. Locating a sound source employing the distance provided by the empirical model is valuable when OBSs are too far apart for 'traditional' multi-sensor methods. In such cases, the incoming direction of the sound source is determined by rotating the horizontal-component OBS seismic data to point to the source back-azimuth. Also, the amplitude decay information provided by the model has multiple applications in other areas where noise pollution may be a concern (e.g., marine infrastructure construction).

To detect damage in mechanical structures, acoustic emission (AE) inspection is considered as a powerful tool. Generally, the classical acoustic emission detection method uses a sparse sensor array to identify damage and its location. It often depends on a pre-defined wave velocity and it is difficult to yield a high localization accuracy for complicated structures using this method. In this paper, the passive guided wave phased array method, a dense sensor array method, is studied, aiming to obtain better AE localization accuracy in aluminum thin plates. Specifically, the proposed method uses a cross-shaped phased array enhanced with four additional far-end sensors for AE source localization. The proposed two-step method first calculates the real-time velocity and the polar angle of the AE source using the phased array algorithm, and then solves the location of the AE source with the additional far-end sensor. Both numerical and physical experiments on an aluminum flat panel are carried out to validate the proposed method. It is found that using the cross-shaped guided wave phased array method with enhanced far-end sensors can localize the coordinates of the AE source accurately without knowing the wave velocity in advance. The proposed method is also extended to a stiffened thin-walled structure with high localization accuracy, which validates its AE source localization ability for complicated structures. Finally, the influences of cross-shaped phased array element number and the time window length on the proposed method are discussed in detail.

Noise from a tactical aircraft can impact operations due to concerns regarding military personnel noise exposure and community annoyance and disturbance. The efficacy of mission planning can increase when the distinct, complex acoustic source mechanisms creating the noise are better understood. For each type of noise, equivalent acoustic source distributions are obtained from a tied-down F-35B operating at various engine conditions using the hybrid method for acoustic source imaging of Padois, Gauthier, and Berry [J. Sound Vib. 333, 6858-6868 (2014)]. The source distributions for the distinct noise types are obtained using different sections of a 71 element, ground-based linear array. Using a subarray close to the nozzle exit plane, source distributions are obtained for fine-scale turbulent mixing noise and broadband shock-associated noise, although grating lobes complicate interpretations at higher frequencies. Results for a subarray spanning the maximum sound region show that the multiple frequency peaks in tactical aircraft noise appear to originate from overlapping source regions. The observation of overlapping spatial extent of competing noise sources is supported by the coherence properties of the source distributions for the different subarrays.

Generation of combustion noise in an unconfined turbulent non-premixed flame is investigated. For this, a model is developed, combining Lighthill's acoustic analogy with a flamelet-based combustion model to consistently express all thermochemical quantities by a set of reduced scalars. The model is applied in a large-eddy simulation, and the acoustic pressure in the far field is obtained from an integral solution. Three relevant acoustic source terms with different source characteristics and Mach number scaling are identified. The spatial distribution and spectral characteristics of the acoustic sources are analyzed, and it is shown that the acoustic source due to chemical reaction is the main noise contributor, and is located in the upper part of the flame. Contributions from the acoustic sources due to Reynolds stresses and fluctuating mass flux are found to be virtually insignificant at low frequencies. Discrepancies in the prediction of high-frequency sound pressure level in the jet forward direction were analyzed and are attributed to high-frequency acoustic refraction effects due to variations in sound speed. The directivity exhibits a weak directionality in the 30° forward direction, and some phase cancellation between individual acoustic sources is evident.

Beamforming is an essential step in the ultrasound image formation pipeline and has recently attracted growing interest. An important goal of beamforming is to increase the image spatial resolution, or in other words to narrow down the system Point Spread Function (PSF). In parallel to beamforming approaches, deconvolution methods have also been explored in ultrasound imaging to mitigate the adverse effects of PSF. Unfortunately, these two steps have only been considered separately in a sequential approach. Herein, a novel framework for unifying beamforming and deconvolution in ultrasound image reconstruction is introduced. More specifically, the proposed formulation is a regularized inverse problem including two linear models for beamforming and deconvolution plus additional sparsity constraint. We take advantage of the alternating direction method of multipliers algorithm to find the solution of the joint optimization problem. The performance evaluation is presented on a set of publicly available simulations, real phantoms, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> data. As compared to Delay-And-Sum (DAS) beamforming, simulation results indicate improvements of 45% and 44% in terms of axial and lateral resolution, respectively. Moreover, the proposed method improves the contrast of simulation data by 6.7% in comparison to DAS. The superiority of the proposed approach in comparison with the sequential approach as well as the state-of-the-art beamforming and deconvolution approaches is also shown.

A broadband equivalent acoustic source distribution can be used to model the sound field near a high-speed jet. Such models must account for the spatiospectral variation of the sound levels. This work presents a technique for obtaining such a model using a spectral decomposition method associated with large and fine-scale turbulent mixing noise to create broadband equivalent source distributions for each noise type. The large-scale turbulent mixing noise is represented by frequency-dependent wavepackets, while the fine-scale turbulent mixing noise is modeled as a frequency-dependent incoherent, extended source distribution. This technique is applied to acoustical measurements from an ideally expanded, unheated Mach 1.8 jet. The wavepackets model the sound field levels in the maximum radiation region, but the second incoherent source distribution is required to obtain the levels at the other locations. The combination of the incoherent source distribution and the wavepacket provides a broadband, equivalent acoustic source representation that adequately models the sound field for Strouhal numbers between 0.04 and 0.25. At higher Strouhal numbers, better agreement is obtained when accounting for a frequency-dependent shift in the apparent acoustic source region. This frequency-dependent source region is more important closer to the jet than in the far field.