Robust expectation-maximization algorithm for multiple wide-band acoustic source localization in the presence of non-uniform noise variances

2010 ◽  
Author(s):  
Lu Lu ◽  
Hsiao-Chun Wu ◽  
Kun Yan
Keyword(s):  
Source Localization ◽  
Expectation Maximization ◽  
Expectation Maximization Algorithm ◽  
Wide Band ◽  
Acoustic Source ◽  
Acoustic Source Localization ◽  
Uniform Noise

Utilizing laser distance sensors for audio recovery and acoustic source localization

2021 ◽  
Vol 149 (4) ◽  
pp. A43-A44
Author(s):  
Kanad Sarkar ◽  
Ryan M. Corey ◽  
Sri Vuppala ◽  
Andrew C. Singer
Keyword(s):  
Source Localization ◽  
Acoustic Source ◽  
Acoustic Source Localization

A fast approach for acoustic source localization on a thin spherical shell

2021 ◽  
pp. 147592172110419
Author(s):  
Zixian Zhou ◽  
Zhiwen Cui ◽  
Tribikram Kundu
Keyword(s):  
Velocity Profile ◽  
Spherical Shell ◽  
Source Localization ◽  
Pressure Vessels ◽  
Solution Technique ◽  
Acoustic Source ◽  
Spherical Shells ◽  
Fast Approach ◽  
Acoustic Source Localization ◽  
Thin Spherical Shell

Thin spherical shell structures are wildly used as pressure vessels in the industry because of their property of having equal in-plane normal stresses in all directions. Since very large pressure difference between the inside and outside of the wall exists, any formation of defects in the pressure vessel wall has a huge safety risk. Therefore, it is necessary to quickly locate the area where the defect maybe located in the early stage of defect formation and make repair on time. The conventional acoustic source localization techniques for spherical shells require either direction-dependent velocity profile knowledge or a large number of sensors to form an array. In this study, we propose a fast approach for acoustic source localization on thin isotropic and anisotropic spherical shells. A solution technique based on the time difference of arrival on a thin spherical shell without the prior knowledge of direction-dependent velocity profile is provided. With the help of “L”-shaped sensor clusters, only 6 sensors are required to quickly predict the acoustic source location for anisotropic spherical shells. For isotropic spherical shells, only 4 sensors are required. Simulation and experimental results show that this technique works well for both isotropic and anisotropic spherical shells.

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