1,583 research outputs found

    Design and Use of Microphone Directional Arrays for Aeroacoustic Measurements

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    An overview of the development of two microphone directional arrays for aeroacoustic testing is presented. These arrays were specifically developed to measure airframe noise in the NASA Langley Quiet Flow Facility. A large aperture directional array using 35 flush-mounted microphones was constructed to obtain high resolution noise localization maps around airframe models. This array possesses a maximum diagonal aperture size of 34 inches. A unique logarithmic spiral layout design was chosen for the targeted frequency range of 2-30 kHz. Complementing the large array is a small aperture directional array, constructed to obtain spectra and directivity information from regions on the model. This array, possessing 33 microphones with a maximum diagonal aperture size of 7.76 inches, is easily moved about the model in elevation and azimuth. Custom microphone shading algorithms have been developed to provide a frequency- and position-invariant sensing area from 10-40 kHz with an overall targeted frequency range for the array of 5-60 kHz. Both arrays are employed in acoustic measurements of a 6 percent of full scale airframe model consisting of a main element NACA 632-215 wing section with a 30 percent chord half-span flap. Representative data obtained from these measurements is presented, along with details of the array calibration and data post-processing procedures

    Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees

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    This paper addresses the problem of ad hoc microphone array calibration where only partial information about the distances between microphones is available. We construct a matrix consisting of the pairwise distances and propose to estimate the missing entries based on a novel Euclidean distance matrix completion algorithm by alternative low-rank matrix completion and projection onto the Euclidean distance space. This approach confines the recovered matrix to the EDM cone at each iteration of the matrix completion algorithm. The theoretical guarantees of the calibration performance are obtained considering the random and locally structured missing entries as well as the measurement noise on the known distances. This study elucidates the links between the calibration error and the number of microphones along with the noise level and the ratio of missing distances. Thorough experiments on real data recordings and simulated setups are conducted to demonstrate these theoretical insights. A significant improvement is achieved by the proposed Euclidean distance matrix completion algorithm over the state-of-the-art techniques for ad hoc microphone array calibration.Comment: In Press, available online, August 1, 2014. http://www.sciencedirect.com/science/article/pii/S0165168414003508, Signal Processing, 201

    Nearfield Acoustic Holography using sparsity and compressive sampling principles

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    Regularization of the inverse problem is a complex issue when using Near-field Acoustic Holography (NAH) techniques to identify the vibrating sources. This paper shows that, for convex homogeneous plates with arbitrary boundary conditions, new regularization schemes can be developed, based on the sparsity of the normal velocity of the plate in a well-designed basis, i.e. the possibility to approximate it as a weighted sum of few elementary basis functions. In particular, these new techniques can handle discontinuities of the velocity field at the boundaries, which can be problematic with standard techniques. This comes at the cost of a higher computational complexity to solve the associated optimization problem, though it remains easily tractable with out-of-the-box software. Furthermore, this sparsity framework allows us to take advantage of the concept of Compressive Sampling: under some conditions on the sampling process (here, the design of a random array, which can be numerically and experimentally validated), it is possible to reconstruct the sparse signals with significantly less measurements (i.e., microphones) than classically required. After introducing the different concepts, this paper presents numerical and experimental results of NAH with two plate geometries, and compares the advantages and limitations of these sparsity-based techniques over standard Tikhonov regularization.Comment: Journal of the Acoustical Society of America (2012

    Optical Geolocation for Small Unmanned Aerial Systems

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    This paper presents an airborne optical geolocation system using four optical targets to provide position and attitude estimation for a sUAS supporting the NASA Acoustic Research Mission (ARM), where the goal is to reduce nuisance airframe noise during approach and landing. A large precision positioned microphone array captures the airframe noise for multiple passes of a Gulfstream III aircraft. For health monitoring of the microphone array, the Acoustic Calibration Vehicle (ACV) sUAS completes daily flights with an onboard speaker emitting tones at frequencies optimized for determining microphone functionality. An accurate position estimate of the ACV relative to the array is needed for microphone health monitoring. To this end, an optical geolocation system using a downward facing camera mounted to the ACV was developed. The 3D positioning of the ACV is computed using the pinhole camera model. A novel optical geolocation algorithm first detects the targets, then a recursive algorithm tightens the localization of the targets. Finally, the position of the sUAS is computed using the image coordinates of the targets, the 3D world coordinates of the targets, and the camera matrix. A Real-Time Kinematic GPS system is used to compare the optical geolocation system

    CABE : a cloud-based acoustic beamforming emulator for FPGA-based sound source localization

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    Microphone arrays are gaining in popularity thanks to the availability of low-cost microphones. Applications including sonar, binaural hearing aid devices, acoustic indoor localization techniques and speech recognition are proposed by several research groups and companies. In most of the available implementations, the microphones utilized are assumed to offer an ideal response in a given frequency domain. Several toolboxes and software can be used to obtain a theoretical response of a microphone array with a given beamforming algorithm. However, a tool facilitating the design of a microphone array taking into account the non-ideal characteristics could not be found. Moreover, generating packages facilitating the implementation on Field Programmable Gate Arrays has, to our knowledge, not been carried out yet. Visualizing the responses in 2D and 3D also poses an engineering challenge. To alleviate these shortcomings, a scalable Cloud-based Acoustic Beamforming Emulator (CABE) is proposed. The non-ideal characteristics of microphones are considered during the computations and results are validated with acoustic data captured from microphones. It is also possible to generate hardware description language packages containing delay tables facilitating the implementation of Delay-and-Sum beamformers in embedded hardware. Truncation error analysis can also be carried out for fixed-point signal processing. The effects of disabling a given group of microphones within the microphone array can also be calculated. Results and packages can be visualized with a dedicated client application. Users can create and configure several parameters of an emulation, including sound source placement, the shape of the microphone array and the required signal processing flow. Depending on the user configuration, 2D and 3D graphs showing the beamforming results, waterfall diagrams and performance metrics can be generated by the client application. The emulations are also validated with captured data from existing microphone arrays.</jats:p

    A novel deconvolution beamforming algorithm for virtual phased arrays

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    Beamforming techniques using phased microphone arrays are one of the most common tools for localizing and quantifying noise sources. However, the use of such devices can result in a series of well-known disadvantages regarding, for instance, their very high cost or transducer mismatch. Virtual Phased Arrays (VPAs) have been proposed as an alternative solution to prevent these difficulties provided the sound field is time stationary. Several frequency domain beamforming techniques can be adapted to only use the relative phase between a fixed and a moving transducer. Therefore the results traditionally obtained using large arrays can be emulated by applying beamforming algorithms to data acquired from only two sensors. This paper presents a novel beamforming algorithm which uses a deconvolution approach to strongly reduce the presence of side lobes. A series of synthetic noise sources with negative source strength are introduced in order to maximize the dynamic range of the beamforming deconvolved map. This iterative sidelobe cleaner algorithm (ISCA) does not require the of use of the covariance matrix of the array, hence it can also be applied to a VPA. The performance of ISCA is compared throughout several simulations with conventional deconvolution algorithms such as DAMAS and NNLS. The results support the robustness and accuracy of the proposed approach, providing clear localization maps in all the conditions evaluated

    Accurate aeroacoustic measurements in closed-section hard-walled wind tunnels

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    Noise emissions from aircraft are of major concern to aircraft manufacturers. There are various analytical, empirical and numerical tools to help in the design of quieter aircraft, however aeroacoustic measurements in wind tunnels are still required. There is a growing interest in simultaneous aerodynamic and aeroacoustic measurements in hard-walled closed-section wind tunnels. The research hypothesis of this work is whether accurate aeroacoustic measurements are possible in this type of wind tunnel. Two issues are of particular concern: the reverberation sound field and high background noise levels. De-reverberation, based on an Image Source Model (ISM), is proposed to tackle the first issue by incorporating the reflections in the focused beamformer. This technique is computationally fast and easy to implement. Source Power Integration and deconvolution techniques are shown to be still valid in de-reverberation. Measurements in a closed section wind tunnel have shown that an ISM gives a better estimate of the Green's functions, when compared to free-space Green's functions. Furthermore de-reverberation yielded more accurate source strength estimates from the beamformer. Qualitatively, de-convolved results were no different than when using free-space Green's functions. Simulations have shown that the ISM can become unstable at high frequencies if position errors are present. It is therefore recommended to limit the application of the ISM to frequencies below 10 kHz. At low frequencies the accuracy of beamforming levels is highly dependent on the level of noise contamination of the input data. Removing the diagonal of the cross spectral matrix might not be sufficient to eliminate this noise

    A Methodology for Acoustic Measurement and Separation of Background Noise

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    An attempt is made at developing experimental methods for the acoustic measurement and separation of background noise in a wind tunnel. To this end, an array beamforming technique known as delay-and- sum beamforming is identified and tested. The theory underlying delay-and-sum beamforming is discussed. Two linear arrays, the seven microphone linear array and the four microphone minimum redundancy array, are designed. A driver is designed based on Helmholtz resonator theory to provide a source of monochromatic sound. Also, the concept of partial coherence as applicable to the separation of background noise from signal noise is investigated. Array beamforming results show that tests conducted with the two linear arrays in the open field provide good resolution of the sound source Direction Of Arrival (DOA) peaks from the background noise, and provide a semianechoic reference with which to compare wind tunnel results. Beamforming results obtained for the driver placed inside the wind tunnel with the tunnel running at 0, 45, and 81 ft/sec successfully resolved the DOA peaks of the driver from the background noise of the tunnel. At a tunnel velocity of 151 ft/sec, the driver signal is completely buried in the background noise of the tunnel, and beamforming was not successful in resolving the peak corresponding to the driver signal
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