Wind turbine noise measurement using a compact microphone array with advanced deconvolution algorithms

This paper experimentally investigates the noise from a large wind turbine (GE 1.5 MW) with a compact microphone array (OptiNav 24) using advanced deconvolution based beamforming methods, such as DAMAS and CLEAN-SC beamforming algorithms, for data reduction. Our study focuses on the ability of a compact microphone array to successfully locate both mechanical and aerodynamic noise sources on the wind turbine. Several interesting results have emerged from this study: (i) A compact microphone array is sufficient to perform a detailed study on wind turbine noise if advanced deconvolution methods are applied. (ii) Noise sources on the blade and on the nacelle can clearly be separated. (iii) Noise of the blades is dominated by trailing edge noise which is frequency dependent and is distributed along the length of the blade with the dominant noise source closer to the tip of the blade. (iv) The LP and DAMAS algorithms represent the distributed trailing edge noise source better than CLEAN-SC and classical beamforming. (v) Additional tonal noise produced during yawing operation is believed to be radiating from the tower of the wind turbine that acts like a resonator. (vi) Ground reflection is not believed to have a significant effect on noise source location estimates in this study.     

A covariance fitting approach for correlated acoustic source mapping

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.     

Sparsity constrained deconvolution approaches for acoustic source mapping

Using microphone arrays for estimating source locations and strengths has become common practice in aeroacoustic applications. The classical delay-and-sum approach suffers from low resolution and high sidelobes and the resulting beamforming maps are difficult to interpret. The deconvolution approach for the mapping of acoustic sources (DAMAS) deconvolution algorithm recovers the actual source levels from the contaminated delay-and-sum results by defining an inverse problem that can be represented as a linear system of equations. In this paper, the deconvolution problem is carried onto the sparse signal representation area and a sparsity constrained deconvolution approach (SC-DAMAS) is presented for solving the DAMAS inverse problem. A sparsity preserving covariance matrix fitting approach (CMF) is also presented to overcome the drawbacks of the DAMAS inverse problem. The proposed algorithms are convex optimization problems. Our simulations show that CMF and SC-DAMAS outperform DAMAS and as the noise in the measurements increases, CMF works better than both DAMAS and SC-DAMAS. It is observed that the proposed algorithms converge faster than DAMAS. A modification to SC-DAMAS is also provided which makes it significantly faster than DAMAS and CMF. For the correlated source case, the CMF-C algorithm is proposed and compared with DAMAS-C. Improvements in performance are obtained similar to the uncorrelated case.     

Imaging of directional distributed noise sources

This study relates to the acoustic imaging of noise sources that are distributed and strongly directional, such as in turbulent jets. The goal is to generate high-resolution noise source maps with self-consistency, i.e., their integration over the extent of the noise source region gives the far-field pressure auto-spectrum for a particular emission direction. Self-consistency is possible by including a directivity factor in the formulation of the source cross-spectral density. The resulting source distribution is based on the complex coherence, rather than the cross-spectrum, of the measured acoustic field. For jet noise, whose spectral nature changes with emission angle, it is necessary to conduct the measurements with a narrow-aperture array. Three coherence-based imaging methods were applied to a Mach 0.9 turbulent jet: delay-and-sum beamforming; deconvolution of the beamformer output; and direct spectral estimation that relies on minimizing the difference between the measured and modeled coherences of the acoustic field. The delay-and-sum beamforming generates noise source maps with strong spatial distortions and sidelobes. Deconvolution leads to a five-fold improvement in spatial resolution and significantly reduces the intensity of the sidelobes. The direct spectral estimation produces maps very similar to those obtained by deconvolution. The coherence-based noise source maps, obtained by deconvolution or direct spectral estimation, are similar at small and large observation angles relative to the jet axis.     

Inverse problem with beamforming regularization matrix applied to sound source localization in closed wind-tunnel using microphone array

Microphone arrays have become a standard technique to localize and quantify source in aeroacoustics. The simplest approach is the beamforming that provides noise source maps with large main lobe and strong side lobes at low frequency. Since a decade, the focus is set on deconvolution techniques such as DAMAS or Clean-SC. While the source map is clearly improved, these methods require a large computation time. In this paper, we propose a sound source localization technique based on an inverse problem with beamforming regularization matrix called Hybrid Method. With synthetic data, we show that the side lobes are removed and the main lobe is narrower. Moreover, if the sound noise source map provided by this method is used as input in the DAMAS process, the number of DAMAS iterations is highly reduced. The Hybrid Method is applied to experimental data obtained in a closed wind-tunnel. In both cases of acoustic or aeroacoustic data, the source is correctly detected. The proposed Hybrid Method is found simple to implement and the computation time is low if the number of scan points is reasonable.     

Uncertainty analysis of the standard delay-and-sum beamformer and array calibration

Beamforming has become an ubiquitous task in aeroacoustic noise measurements for source localization and power estimation. The standard delay-and-sum (DAS) beamformer is the most commonly used beamforming algorithm due to its simplicity and robustness and also serves as the basis for more sophisticated algorithms, such as the deconvolution approach for the mapping of acoustic sources (DAMAS). The DAS data reduction equation is a function of many parameters including the microphone locations, microphone transfer functions, temperature and the cross-spectral matrix (CSM), where each one of these parameters has a unique uncertainty associated with it. This paper provides a systematic uncertainty analysis of the DAS beamformer and Dougherty's widely used calibration procedure under the assumption that the underlying mathematical model of incoherent, monopole sources is correct. An analytical multivariate method based on a first-order Taylor series expansion and a numerical Monte-Carlo method based on assumed uncertainty distributions for the input variables are considered. The uncertainty of calibration is analyzed using the Monte-Carlo method, whereas the uncertainty of the DAS beamformer is analyzed using both the complex multivariate and the Monte-Carlo methods. It is shown that the multivariate uncertainty analysis method fails when the perturbations are relatively large and/or the output distribution is non-Gaussian, and therefore the Monte-Carlo analysis should be used in the general case. The calibration procedure is shown to greatly reduce the uncertainties in the DAS power estimates. In particular, 95 percent confidence intervals for the DAS power estimates are presented with simulated data for various scenarios. Moreover, the 95 percent confidence intervals for the integrated DAS levels at different frequencies are computed using experimental data. It is shown that with experimental data, the 95 percent confidence intervals for the integrated power levels are within of the mean levels when the component uncertainties are set at low but achievable values.     

A fast signal subspace approach for the determination of absolute levels from phased microphone array measurements

Phased microphone arrays are used in a variety of applications for the estimation of acoustic source location and spectra. The popular conventional delay-and-sum beamforming methods used with such arrays suffer from inaccurate estimations of absolute source levels and in some cases also from low resolution. Deconvolution approaches such as DAMAS have better performance, but require high computational effort. A fast beamforming method is proposed that can be used in conjunction with a phased microphone array in applications with focus on the correct quantitative estimation of acoustic source spectra. This method bases on an eigenvalue decomposition of the cross spectral matrix of microphone signals and uses the eigenvalues from the signal subspace to estimate absolute source levels. The theoretical basis of the method is discussed together with an assessment of the quality of the estimation. Experimental tests using a loudspeaker setup and an airfoil trailing edge noise setup in an aeroacoustic wind tunnel show that the proposed method is robust and leads to reliable quantitative results.     

L1 generalized inverse beam-forming algorithm resolving coherent/incoherent, distributed and multipole sources

To resolve coherent/incoherent, distributed/compact, and multipole aerodynamic-sound sources with phased-array pressure data, a new source-detection algorithm is developed based on L₁ generalized inverse techniques. To extract each coherent signal, a cross spectral matrix is decomposed into eigenmodes. Subsequently, the complex source-amplitude distribution that recovers each eigenmode is solved using generalized inverse techniques with reference solutions which include multipoles as well as a monopole. Namely, the source distribution consisting of pre-defined source types is solved as an L₁ norm problem using iteratively re-weighted least squares (IRLS). The capabilities of the proposed algorithm are demonstrated using various benchmark problems to compare the results with several existing beam-forming algorithms, and it is found that distributed sources as well as dipoles with arbitrary orientation can be identified regardless of coherency with another source. The resolution is comparable to existing deconvolution techniques, such as DAMAS or CLEAN, and the computational cost is only several times more than that of DAMAS2. The proposed algorithm is also examined using previous model-scale test data taken in an open-jet wind-tunnel for a study on jet-flap interaction, and some indication of dipole radiation is discerned near the flap edge.     

A numerical optimization approach to acoustic hull array design

A numerical optimization approach is presented to optimize passive broadband detection performance of hull arrays through the adjustment of array shading weights. The approach is developed for general hull arrays in low signal-to-noise ratio scenarios, and is shown to converge rapidly to optimal solutions that maximize the array's deflection coefficient. The beamformer is not redesigned in this approach; only the shading weights of the conventional beamformer are adjusted. This approach allows array designers to use the array to minimize the impact of known sources of noise on detection at the beamformer output while maintaining acoustic array gain against an unknown source. The technique is illustrated through numerical examples using hull-borne structural noise as the noise source; however, the design concept can be applied to other design parameters of the array such as element position, material selection, etc.     

ARJ21客机降落阶段起落架噪声试验研究

为了测量ARJ21客机的起落架噪声,在飞行现场分别采用改进的频域波束形成和解卷积算法对降落阶段的起落架噪声进行了测量。通过比较两种算法发现,解卷积算法比改进的频域波束形成算法具有更好的声源识别能力。为了提高传声器的利用率,设计了多臂螺旋阵,并且利用线性插值消除了多普勒效应。根据主起落架和前起落架的分布位置不同,将声源识别区域划分为两部分,在140—800Hz范围内对不同频段的1/3倍频程的起落架噪声进行了测量。结果发现:在250 Hz以上频段,主起落架为主要噪声源,且在中心频率500 Hz的1/3倍频程内为唯一强声源;前起落架在中心频率630 Hz的1/3倍频程内为主要噪声源。通过试验得到了主起落架和前起落架噪声在不同频段的分布特点,为起落架降噪设计提供了支持。     

Irregular array motion and extended integration for the suppression of spatial aliasing in passive sonar

Conventional synthetic aperture processing uses motion of the sonar to increase aperture size and bearing resolution. Two recent papers discussed a different application in which synthetic elements are used to fill in an otherwise sparse passive array. This paper points out that ambiguities persist, even with synthetic elements, in the ideal case of a straight, uniform, sparse line array with constant velocity in the presence of plane wave signals. It is also shown that irregular motion such as acceleration introduces additional information which can be exploited to suppress the ambiguities. The degree of suppression in such an approach is independent of signal direction. If source stability supports extended coherent integration, then the acceleration and integration time required are both modest to achieve interesting levels of suppression. For a less stable source, a modified conventional beamformer is introduced which leverages acceleration over multiple snapshots to suppress the ambiguities. A post-beamformed processing stage involving a nonlinear deconvolution technique such as the CLEAN algorithm can further improve the result. A semi-coherent adaptation of CLEAN is shown to remove the residual ambiguities effectively in the presence of a moderate level of uncorrelated noise.     

Evidence of Doppler-shifted Bragg scattering in the vertical plane by ocean surface waves

A set of narrowband tones (280, 370, 535, and 695 Hz) were transmitted by an acoustic source mounted on the ocean floor in 10 m deep water and received by a 64-element hydrophone line array lying on the ocean bottom 1.25 km away. Beamformer output in the vertical plane for the received acoustic tones shows evidence of Doppler-shifted Bragg scattering of the transmitted acoustic signals by the ocean surface waves. The received, scattered signals show dependence on the ocean surface wave frequencies and wavenumber vectors, as well as on acoustic frequencies and acoustic mode wavenumbers. Sidebands in the beamformer output are offset in frequency by amounts corresponding to ocean surface wave frequencies. Deviations in vertical arrival angle from specular reflection agree with those predicted by the Bragg condition through first-order perturbation theory using measured directional surface wave spectra and acoustic modes measured by the horizontal hydrophone array.     

Bayesian multiple-source localization in an uncertain ocean environment

This paper considers simultaneous localization of multiple acoustic sources when properties of the ocean environment (water column and seabed) are poorly known. A Bayesian formulation is developed in which the environmental parameters, noise statistics, and locations and complex strengths (amplitudes and phases) of multiple sources are considered to be unknown random variables constrained by acoustic data and prior information. Two approaches are considered for estimating source parameters. Focalization maximizes the posterior probability density (PPD) over all parameters using adaptive hybrid optimization. Marginalization integrates the PPD using efficient Markov-chain Monte Carlo methods to produce joint marginal probability distributions for source ranges and depths, from which source locations are obtained. This approach also provides quantitative uncertainty analysis for all parameters, which can aid in understanding of the inverse problem and may be of practical interest (e.g., source-strength probability distributions). In both approaches, closed-form maximum-likelihood expressions for source strengths and noise variance at each frequency allow these parameters to be sampled implicitly, substantially reducing the dimensionality and difficulty of the inversion. Examples are presented of both approaches applied to single- and multi-frequency localization of multiple sources in an uncertain shallow-water environment, and a Monte Carlo performance evaluation study is carried out.     

Performance of an adaptive beamforming noise reduction scheme for hearing aid applications. I. Prediction of the signal-to-noise-ratio improvement

Adaptive beamformers have been proposed as noise reduction schemes for conventional hearing aids and cochlear implants. A method to predict the amount of noise reduction that can be achieved by a two-microphone adaptive beamformer is presented. The prediction is based on a model of the acoustic environment in which the presence of one acoustic target-signal source and one acoustic noise source in a reverberant enclosure is assumed. The acoustic field is sampled using two omnidirectional microphones mounted close to the ears of a user. The model takes eleven different parameters into account, including reverberation time and size of the room, directionality of the acoustic sources, and design parameters of the beamformer itself, including length of the adaptive filter and delay in the target signal path. An approximation to predict the achievable signal-to-noise improvement based on the model is presented. Potential applications as well as limitations of the proposed prediction method are discussed and a FORTRAN subroutine to predict the achievable signal-to-noise improvement is provided. Experimental verification of the predictions is provided in a companion paper [J. Acoust. Soc. Am. 109, 1134 (2001)].     

An experimental comparison of the focused beamformer and the inverse method for the characterisation of acoustic sources in ideal and non-ideal acoustic environments

The current availability and affordability of multi-microphone array systems has awakened a strong interest in sound source location and characterisation in many fields of experimental acoustics and noise control. Although the theory behind the design of such arrays has been known for some time, the algorithms used to process the microphone signals are the subject of on-going research and development. The beamformer algorithm is well-known and relatively simple to implement. It is useful for ‘scanning’ an area to find the position of sound sources but has limited ability to characterise fully the spatial distribution of the strength of an acoustic source. The inverse method, on the other hand, requires prior information regarding the position of sources or an appropriate discretisation of the source strength distribution. The method is more difficult to implement but can yield more useful source characterisation data. This paper presents a comparison between the two methods based on experimental data. The results show that, in the presence of more than one source, the beamformer cannot yield reliable estimates of the source strength of individual sources since the output from the beamformer is shown to be dependent upon the degree of correlation between multiple sources as well as the source strengths themselves. The inverse method, on the other hand, is shown to yield reliable estimates of source strength when more than one source is present, regardless of the correlation between the sources, although the results presented here are restricted to the case of a relatively small number of sources. It is clearly demonstrated, both theoretically and through carefully controlled experiments, that either method can be used effectively under reverberant conditions through the use of measured Green functions in place of the simple geometrically-derived free-space values of the Green function. This greatly improves the possibility for the successful use of these methods in many important industrial applications.     

利用宽带声场频率-掠射角干涉结构的深海直达声区目标深度估计方法

针对典型深海环境中宽带声源的深度分辨问题,通过研究深海声场随频率起伏的干涉结构与垂直线阵频域波束输出图中的干涉结构,给出一种直达声区内可区分多水下目标的宽带声源深度估计方法。该方法以近水面目标的射线声场模型为基础,推导出近海面宽带声源接收声场的波束输出表达式,阐明了频域波束输出图中干涉结构与声源深度的对应关系。然后利用改进的傅里叶变换方法将二维频域波束输出图映射到声源深度-掠射角度域,可实现声源深度信息的有效分离。最后开展了深海实验验证,利用垂直阵接收拖曳声源发射的宽带白噪声信号,拖曳声源深度计算结果与实测声源深度基本一致。数值仿真与实验结果均表明该方法可以在多目标复杂环境下准确估计出水下宽带声源的深度。     

Flap-edge aeroacoustic measurements and predictions

An aeroacoustic model test has been conducted to investigate the mechanisms of sound generation on high-lift wing configurations. This paper presents an analysis of flap side-edge noise, which is often the most dominant source. A model of a main element wing section with a half-span flap was tested at low speeds of up to a Mach number of 0.17, corresponding to a wing chord Reynolds number of approximately 1.7 million. Results are presented for flat (or blunt), flanged, and round flap-edge geometries, with and without boundary-layer tripping, deployed at both moderate and high flap angles. The acoustic database is obtained from a small aperture directional array (SADA) of microphones, which was constructed to electronically steer to different regions of the model and to obtain farfield noise spectra and directivity from these regions. The basic flap-edge aerodynamics is established by static surface pressure data, as well as by computational fluid dynamics (CFD) calculations and simplified edge flow analyses. Distributions of unsteady pressure sensors over the flap allow the noise source regions to be defined and quantified via cross-spectral diagnostics using the SADA output. It is found that shear layer instability and related pressure scatter is the primary noise mechanism. For the flat edge flap, two noise prediction methods based on unsteady-surface-pressure measurements are evaluated and compared to measured noise. One is a new causality spectral approach developed here. The other is a new application of an edge-noise scatter prediction method. The good comparisons for both approaches suggest that the prediction models capture much of the physics. Areas of disagreement appear to reveal when the assumed edge noise mechanism does not fully define the noise production. For the different edge conditions, extensive spectra and directivity are presented. The complexity of the directivity results demonstrate the strong role of edge source geometry and frequency in the noise radiation. Significantly, for each edge configuration, the spectra for different flow speeds, flap angles, and surface roughness were successfully scaled by utilizing aerodynamic performance and boundary-layer scaling methods developed herein.     

Planar near-field acoustical holography in a moving medium

Near-field acoustical holography (NAH) is a well-established method to study acoustic radiation near a stationary sound source in a homogeneous, stationary medium. However, the current theory of NAH is not applicable to moving sound sources, such as automobiles and trains. In this paper, the inclusion of a moving medium (i.e., moving source and receiver) is introduced in the wave equation and a new set of equations for plannar NAH is developed. Equations are developed for the acoustic pressure, particle velocity, and intensity when mean flow is either parallel or perpendicular to the hologram plane. If the source and the measurement plane are moving at the same speed, the frequency Doppler effect is absent, but a wave number Doppler effect exists. This leads to errors when reconstructing the acoustic field both towards and away from the source using static NAH. To investigate these errors, a point source is studied analytically using planar NAH with flow in one direction. The effect of the medium moving parallel to the hologram plane is noted by a shift of the radiation circle in wave number space (k-space). A k-space Green's function and a k-space filter are developed that include the effects of the moving medium.     

航行船舶噪声源辐射部位定位实验研究

为了有效解决运动船舶目标噪声源辐射部位定位问题,通过采用短时积分,分频段能量融合、噪声源相对位置分析等方法克服目标运动的不利因素,提出采用高频段精确定位的常规聚焦波束形成声图法与中低频段精确定位的频域MVDR (MinimumVariance Distortionless Response)波束形成声图法相结合的定位方法。通过海试数据处理验证了该方法可以有效实现目标噪声源辐射部位近场高分辨定位。在进行大型船海试数据处理时,采用分频段、分时间段,并与船体结构布局相结合的方法,分别给出了主要的噪声源辐射部位(螺旋桨、推进电机+柴油发电机、泵舱)的位置,验证了该实验数据处理方法的实用性。     

双边相关变换在估计水下噪声源波达方向中的应用

研究双边相关变换高分辨率波束成形去估计水下噪声源波达方向的方法和性能,提出了对水下运动目标进行精确定向的一种高精度定向算法,用分割频带中的能量最大频段的窄带定向结果作为初始角,宽带中的高频分割频带作为处理对象来获得较高的定向精度。仿真数据和实际数据表明,该算法是一种花费时间少、定向精度高、简便实用的宽带定向方法。这种高精度的测向算法为水下两基阵交会测距提供了保证。