Robust time-domain processing of broadband microphone array data

1995 ◽  
Vol 3 (3) ◽  
pp. 193-203 ◽  
Author(s):  
M.W. Hoffman ◽  
K.M. Buckley
Keyword(s):  
Time Domain ◽  
Microphone Array ◽  
Array Data

Open-source software for the application of microphone array methods

2017 ◽  
Vol 48 (3-4) ◽  
pp. 44-51 ◽  
Author(s):  
Gert Herold ◽  
Ennes Sarradj
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Time Domain ◽  
Microphone Array ◽  
Synthetic Data ◽  
Object Oriented ◽  
Source Characterization ◽  
Acoustic Source ◽  
Array Data ◽  
Flexible Programming

The open-source Python library Acoular is aimed at the processing of microphone array data. It features a number of algorithms for acoustic source characterization in time domain and frequency domain. The modular, object-oriented architecture allows for flexible programming and a multitude of applications. This includes the processing of measured array data, the mapping of sources, the filtering of subcomponent noise, and the generation of synthetic data for test purposes. Several examples illustrating its versatility are given, as well as one example for implementing a new algorithm into the package.

Separating Multiple Moving Sources by Microphone Array Signals for Wayside Acoustic Fault Diagnosis

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Wei Xiong ◽  
Qingbo He ◽  
Zhike Peng
Keyword(s):  
Fault Diagnosis ◽  
Time Domain ◽  
Feature Matching ◽  
Matching Pursuit ◽  
Microphone Array ◽  
Time Frequency ◽  
Moving Sources ◽  
The Time Domain ◽  
Envelope Spectrum ◽  
Threshold Setting

Wayside acoustic defective bearing detector (ADBD) system is a potential technique in ensuring the safety of traveling vehicles. However, Doppler distortion and multiple moving sources aliasing in the acquired acoustic signals decrease the accuracy of defective bearing fault diagnosis. Currently, the method of constructing time-frequency (TF) masks for source separation was limited by an empirical threshold setting. To overcome this limitation, this study proposed a dynamic Doppler multisource separation model and constructed a time domain-separating matrix (TDSM) to realize multiple moving sources separation in the time domain. The TDSM was designed with two steps of (1) constructing separating curves and time domain remapping matrix (TDRM) and (2) remapping each element of separating curves to its corresponding time according to the TDRM. Both TDSM and TDRM were driven by geometrical and motion parameters, which would be estimated by Doppler feature matching pursuit (DFMP) algorithm. After gaining the source components from the observed signals, correlation operation was carried out to estimate source signals. Moreover, fault diagnosis could be carried out by envelope spectrum analysis. Compared with the method of constructing TF masks, the proposed strategy could avoid setting thresholds empirically. Finally, the effectiveness of the proposed technique was validated by simulation and experimental cases. Results indicated the potential of this method for improving the performance of the ADBD system.

Wavepacket noise source model for microphone array data analysis of hot supersonic jets

2013 ◽  
Vol 134 (5) ◽  
pp. 4127-4127 ◽  
Author(s):  
Philip Morris ◽  
Robert Dougherty ◽  
Chris Nelson ◽  
Alan Cain ◽  
Kenneth Brentner
Keyword(s):  
Data Analysis ◽  
Noise Source ◽  
Microphone Array ◽  
Source Model ◽  
Supersonic Jets ◽  
Array Data

Predictive processing of array acoustic waveform data

Geophysics ◽  
1997 ◽  
Vol 62 (6) ◽  
pp. 1710-1714 ◽  
Author(s):  
Xiao Ming Tang
Keyword(s):  
Time Domain ◽  
Predictive Processing ◽  
Multiple Wave ◽  
Data Set ◽  
Waveform Data ◽  
Array Data ◽  
Wave Data ◽  
Minimization Procedure ◽  
The Time Domain ◽  
Wave Modes

Estimation of wave velocity (or slowness) from array waveform data is a basic and very important process in acoustic logging and seismic processing. A predictive method is developed to process array waveform data containing multiple wave modes. These wave modes may overlap in both time and frequency and are inseparable using conventional techniques. In this new technique, the waveform at a receiver is modeled by a combination of wave data at other receivers using a time‐domain prediction theory. It is assumed that the array data contain a number of propagating modes. A minimization procedure is formulated to optimize the match between the predicted and measured waveforms, yielding slowness estimates of the wave modes across the array. Most important, the optimization is performed directly in the time domain using the entire array wave data set, including all possible data combinations. This strategy effectively reduces the noise effects and enhances the robustness of the estimation. Furthermore, the estimated slowness values can be used in formulating a procedure to split the array data into individual wave modes, allowing their behavior to be analyzed. Examples are shown to demonstrate the ability of the technique to extract wave slowness from multiple wavemode data.

scholarly journals Perceptual Evaluation of Mitigation Approaches of Impairments due to Spatial Undersampling in Binaural Rendering of Spherical Microphone Array Data

2020 ◽  
Vol 68 (6) ◽  
pp. 428-440
Author(s):  
Tim Lübeck ◽  
Hannes Helmholz ◽  
Johannes M. Arend ◽  
Christoph Pörschmann ◽  
Jens Ahrens
Keyword(s):  
Microphone Array ◽  
Array Data ◽  
Perceptual Evaluation

Reconstruction of the Force Applied to a Plate in the Time Domain From Sound Pressure Measurements

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Chuan-Xing Bi ◽  
Long Hu ◽  
Yong-Bin Zhang ◽  
Xiao-Zheng Zhang
Keyword(s):  
Time Domain ◽  
Sound Pressure ◽  
Microphone Array ◽  
Near Field ◽  
Impulse Response Function ◽  
Time History ◽  
Pressure Measurements ◽  
Concentrated Force ◽  
Vibration Responses ◽  
The Time Domain

Abstract This paper provides a non-contact approach to reconstruct the distributed or concentrated force applied to a plate in the time domain. This approach is based on sound pressure measurements and is realized by coupling the techniques of real-time near-field acoustic holography (RT-NAH) and force reconstruction. A microphone array is used to measure the sound pressures in the near field of the plate. The measured sound pressures are taken as the inputs of the RT-NAH to reconstruct the vibration responses, including the normal acceleration, velocity, and displacement, on the surface of the plate. With the reconstructed vibration responses, the equation of motion governing the forced vibration can be further processed to reconstruct the force applied to the plate in the time domain. In the process of reconstructing the vibration responses, a displacement–pressure impulse response function is derived for the first time and is used in the RT-NAH. Results of numerical simulations as well as experiments demonstrate that the proposed approach can identify the location of the force accurately and reconstruct the time history of the force effectively, thereby helping to diagnose the mechanical cause of the radiated noise.

scholarly journals The Application of a Linear Microphone Array in the Quantitative Evaluation of the Blade Trailing-Edge Noise Reduction

2021 ◽  
Vol 11 (2) ◽  
pp. 572
Author(s):  
Weijie Chen ◽  
Luqin Mao ◽  
Kangshen Xiang ◽  
Fan Tong ◽  
Weiyang Qiao
Keyword(s):  
Noise Reduction ◽  
Quantitative Evaluation ◽  
Microphone Array ◽  
Experimental Studies ◽  
Flow Speed ◽  
Aerodynamic Noise ◽  
Noise Sources ◽  
Trailing Edge ◽  
Array Data ◽  
Clean Algorithm

This paper concerns the application of a linear microphone array in the quantitative evaluation of blade trailing-edge (TE) noise reduction. The noise radiation from the blades with straight and serrated TEs is measured in an indoor open-jet wind tunnel. The array data are processed using the inverse method based on the Clean algorithm based on spatial source coherence (Clean-SC). In order to obtain correct application and achieve the best effect for the microphone array test, the computing software for array data reduction is firstly developed and assessed by Sarradj’s benchmark case. The assessment results show that the present array data processing method has a good accuracy with an error less than 0.5 dB in a wide frequency range. Then, a linear array with 32 microphones is designed to identify the noise source of a NACA65(12)-10 blade. The performance of the Clean-SC algorithm is compared with the Clean algorithm based on point spread functions (Clean-PSF) method for experimentally identifying the noise sources of the blade. The results show that there is about a 2 dB error when using the Clean-PSF algorithm due to the interference of different aerodynamic noise sources. Experimental studies are conducted to study the blade TE noise reduction using serrated TEs. The TE noise for the blade with and without sawtooth configurations is measured with the flow speeds from 20 m/s to 70 m/s, and the corresponding Reynolds numbers based on the chord are from 200,000 to 700,000. Parametric studies of the sawtooth amplitude and wavelength are conducted to understand the noise reduction law. It is observed that the TE noise reduction is sensitive to both the amplitude and wavelength. The flow speed also affects the noise reduction in the serrated TEs. To obtain the best noise suppression effect, the sawtooth configuration should be carefully designed according to the actual working conditions and airflow parameters.

scholarly journals Time Domain Spherical Harmonic Processing with Open Spherical Microphones Recording

2021 ◽  
Vol 11 (3) ◽  
pp. 1074
Author(s):  
Huiyuan Sun ◽  
Thushara D. Abhayapala ◽  
Prasanga N. Samarasinghe
Keyword(s):  
Time Domain ◽  
Spherical Harmonic ◽  
Microphone Array ◽  
Sound Field ◽  
Microphone Arrays ◽  
Spatial Audio ◽  
Harmonic Decomposition ◽  
Spherical Harmonic Decomposition ◽  
The Time Domain ◽  
Spherical Microphone Arrays

Spherical harmonic analysis has been a widely used approach for spatial audio processing in recent years. Among all applications that benefit from spatial processing, spatial Active Noise Control (ANC) remains unique with its requirement for open spherical microphone arrays to record the residual sound field throughout the continuous region. Ideally, a low delay spherical harmonic recording algorithm for open spherical microphone arrays is desired for real-time spatial ANC systems. Currently, frequency domain algorithms for spherical harmonic decomposition of microphone array recordings are applied in a spatial ANC system. However, a Short Time Fourier Transform is required, which introduces undesirable system delay for ANC systems. In this paper, we develop a time domain spherical harmonic decomposition algorithm for the application of spatial audio recording mainly with benefit to ANC with an open spherical microphone array. Microphone signals are processed by a series of pre-designed finite impulse response (FIR) filters to obtain a set of time domain spherical harmonic coefficients. The time domain coefficients contain the continuous spatial information of the residual sound field. We corroborate the time domain algorithm with a numerical simulation of a fourth order system, and show the proposed method to have lower delay than existing approaches.

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