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A beamform grid and a phased array of microphones
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Beamforming is an imaging technique that has found many applications in aeroacoustics, and continues to evolve to meet greater challenges. It has elements in common with other methods such as nearfield acoustic holography, but its strength is distributed, broadband, incoherent sources at arbitrary distance from the array. The formulation of the cla...
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The signal quality at different microphone locations varies for distributed microphone arrays. Such microphone constellations require a suitable beamformer design that considers these differences in the input signal conditions. In this paper a frequency domain minimum variance (MV) beamforming approach is presented that uses a soft reference select...
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... Acoustic imaging aims to obtain a visualized sound map from the radiating objects, which has a wide range of applications in source identification, vibration analysis and machine diagnosis [9,13]. It is generally accepted that the beamforming [4,10] and Near-field Acoustical Holography (NAH) [15] are two most widely exploited methods dedicated to the aforementioned issues. A fundamental limitation of acoustic source imaging is imposed by geometry of the array. ...
... Algorithm 1 Nuclear Norm minimization by FISTA 1: Starts with G 0 = S 0 = 0 ∈ C MP×MP , t 1 = 1; µ is step size, λ 0 is an initial regularization parameter and λ d is the final regularization parameter, and η is the radio to decrease λ k−1 in each step. 2: While λ k ≥ λ d do 3: For 1 : N m (N m is the maximum iteration steps for each regularization) 4 In order to design a far field array, the array resolution and spatial aliasing must be taken into account. Array resolution specifies how well an array is able to resolve the direction of propagation. ...
Acoustic beamforming consists in measuring the sound field by the microphone array and infers the source strength in conjunction with the propagation model. A fundamental limitation of acoustic beamforming is determined by the aperture size of the array and the microphone density. In order to extend the working frequency range of conventional phased array beamforming, the sound sources are scanned by moving sequentially a small prototype array, resulting in a large array and high microphone density measurements, which is referred to as non-synchronous measurements beamforming. The main issue of non-synchronous measurements beamforming is that the phase relationships between consecutive snapshots of non-synchronous measurements are missing and result in missing entries in the spectral matrix, however, complete spectral matrix information is crucial for high quality image of beamforming. Thus, non-synchronous measurements beamforming boils down to a spectral matrix completion problem which is modeled by a structured low rank model and solved by designed fast iteration algorithm. In particular, the structured low rank model is constructed by two ingredients: (1) the low rank property of the spectral matrix and (2) the continuity of the acoustic field. The simulation results show the non-synchronous measurements beamforming extended the working frequency range of given small phased array from $2-2.8$ kHz to $1.6-4.5$ kHz with only $9$ times non-synchronous measurements.
... Beamforming is convenient because it works from a shaped array. The basic algorithm is detailed in [1]. This article first deals with this localization method. ...
The capacity of hardware today allows carrying out noise sources locali-sation without moving the microphone array at a limited financial and time cost. The single shot measurement processed with beamforming is comfortable for the user. But the quality of the results limits the interest of such systems: bad resolution, low dynamics and no quantitative levels. This article proposes complementary methods to beamforming to improve the results based on the same single measurement. First a near field beamforming algorithm is developed improving the resolution, and then an inverse method is applied based on the transfer function between the sources and the acoustic pressure at microphone positions or on the hologram in order to "clean" the localisation map and give quantitative results.
This paper proposes a non-contact measurement technique for health monitoring of wind turbine blades using acoustic beamforming techniques. The technique works by mounting an audio speaker inside a wind turbine blade and observing the sound radiated from the blade to identify cracks or damages within the structure. The structural damage or cracks on the surface of a composite wind turbine blade can result in changes in the sound radiation characteristics of the structure. Two preliminary measurements were carried out on a composite box and a section of a wind turbine blade to validate the methodology. The composite box and the blade contained holes of differing dimensions and line cracks. An array with 62 microphones is used to measure the sound radiation from the structures when the speaker is working inside the box and blade. A phased array beamforming technique and CLEAN-based Subtraction of Point spread function from a Reference (CLSPR) are employed to locate the damages on both composite box and the wind turbine blade. Another experiment using a commercially available 48 channel acoustic ring array is also used to compare the results. It is shown that acoustic beamforming and CLSPR can be used to identify the location of the damages in the sample structures with high fidelity.
Localization of the sound source using microphone arrays is largely done by Acoustical Holography or Beamforming method. In this paper we present an implementation of Delay-And-Sum algorithm for beamforming computation using various microphone arrays. A MATLAB code was implemented for postprocessing of obtained acoustic signals. There is also included a description of the fractional delay filter implementation to delay the signal samples by racional values of sample period. The goal of this paper was comparing the accuracy of the source localization with the microphone arrays using small number of microphones. The results of the localization of several noise sources by the different types of arrays is presented.
