Machine listening in combination with microphone arrays for noise source localization and identification

2017 ◽  
Vol 141 (5) ◽  
pp. 3964-3964
Author(s):  
Markus Müller-Trapet ◽  
Jordan Cheer ◽  
Filippo M. Fazi ◽  
Julie Darbyshire ◽  
J. Duncan Young
Keyword(s):  
Source Localization ◽  
Noise Source ◽  
Microphone Arrays ◽  
Machine Listening

Correction: Broadband Airfoil-Noise Source Localization by Microphone Arrays and Modeling of a Swept Free-Tip Blade

2018 ◽  
Author(s):  
Gyuzel R. Yakhina ◽  
Michel Roger ◽  
Arthur Finez ◽  
Valentin Baron ◽  
Stephane Moreau ◽  
...  
Keyword(s):  
Source Localization ◽  
Noise Source ◽  
Microphone Arrays

Broadband Airfoil-Noise Source Localization by Microphone Arrays and Modeling of a Swept Free-Tip Blade

2018 ◽  
Author(s):  
Gyuzel R. Yakhina ◽  
Michel Roger ◽  
Arthur Finez ◽  
Valentin Baron ◽  
Stephane Moreau ◽  
...  
Keyword(s):  
Source Localization ◽  
Noise Source ◽  
Microphone Arrays

scholarly journals Frequency-dependent jet noise source localization using cross-correlation between near and far-field microphone arrays

2017 ◽  
Author(s):  
Jacob A. Ward ◽  
S. Hales Swift ◽  
Kent L. Gee ◽  
Tracianne B. Neilsen ◽  
Koji Okamoto ◽  
...  
Keyword(s):  
Source Localization ◽  
Cross Correlation ◽  
Noise Source ◽  
Jet Noise ◽  
Microphone Arrays ◽  
Far Field ◽  
Frequency Dependent

scholarly journals Acoustic source localization using the open spherical microphone array in the low-frequency range

2019 ◽  
Vol 283 ◽  
pp. 04001
Author(s):  
Boquan Yang ◽  
Shengguo Shi ◽  
Desen Yang
Keyword(s):  
Source Localization ◽  
Generalized Inverse ◽  
Microphone Array ◽  
Low Frequency ◽  
Poor Performance ◽  
Microphone Arrays ◽  
Three Dimension ◽  
Frequency Range ◽  
Array Aperture ◽  
Regularization Matrix

Recently, spherical microphone arrays (SMA) have become increasingly significant for source localization and identification in three dimension due to its spherical symmetry. However, conventional Spherical Harmonic Beamforming (SHB) based on SMA has limitations, such as poor resolution and high side-lobe levels in image maps. To overcome these limitations, this paper employs the iterative generalized inverse beamforming algorithm with a virtual extrapolated open spherical microphone array. The sidelobes can be suppressed and the main-lobe can be narrowed by introducing the two iteration processes into the generalized inverse beamforming (GIB) algorithm. The instability caused by uncertainties in actual measurements, such as measurement noise and configuration problems in the process of GIB, can be minimized by iteratively redefining the form of regularization matrix and the corresponding GIB localization results. In addition, the poor performance of microphone arrays in the low-frequency range due to the array aperture can be improved by using a virtual extrapolated open spherical array (EA), which has a larger array aperture. The virtual array is obtained by a kind of data preprocessing method through the regularization matrix algorithm. Both results from simulations and experiments show the feasibility and accuracy of the method.

Acoustic beamforming for noise source localization – Reviews, methodology and applications

2019 ◽  
Vol 120 ◽  
pp. 422-448 ◽  
Author(s):  
Paolo Chiariotti ◽  
Milena Martarelli ◽  
Paolo Castellini
Keyword(s):  
Source Localization ◽  
Noise Source

Inverse methods in aeroacoustic three-dimensional volumetric noise source localization and quantification

2020 ◽  
Vol 473 ◽  
pp. 115208 ◽  
Author(s):  
G. Battista ◽  
P. Chiariotti ◽  
M. Martarelli ◽  
P. Castellini
Keyword(s):  
Source Localization ◽  
Noise Source ◽  
Three Dimensional ◽  
Inverse Methods

Design and assessment of multiple-sound source localization using microphone arrays

2019 ◽  
Author(s):  
Daniel Gabriel ◽  
Ryosuke Kojima ◽  
Kotaro Hoshiba ◽  
Katsutoshi Itoyama ◽  
Kenji Nishida ◽  
...  
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Microphone Arrays ◽  
Sound Source Localization
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