2006
DOI: 10.1121/1.2336762
|View full text |Cite
|
Sign up to set email alerts
|

Volumetric acoustic vector intensity imager

Abstract: A new measurement system, consisting of a mobile array of 50 microphones that form a spherical surface of radius 0.2 m, that images the acoustic intensity vector throughout a large volume is discussed. A simultaneous measurement of the pressure field across all the microphones provides time-domain holograms. Spherical harmonic expansions are used to convert the measured pressure into a volumetric vector intensity field on a grid of points ranging from the origin to a maximum radius of 0.4 m. Displays of the vo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
20
0

Year Published

2009
2009
2021
2021

Publication Types

Select...
5
3
1

Relationship

0
9

Authors

Journals

citations
Cited by 37 publications
(20 citation statements)
references
References 18 publications
0
20
0
Order By: Relevance
“…Equation (19) corresponds to the least squares solution of the problem with Tikhonov regularization. 22,33 The right inverse is chosen because it is more efficient computationally for an underdetermined problem like the one addressed here ðL > MÞ, given the dimensions of the product G Although the ' 2 -norm solution is chosen in this work, there are alternative solutions, such as the ' 1 -norm, 14 that promote sparse solutions, i.e., few non-zero coefficients, implicitly acting as a regularization penalty.…”
Section: B Regularized Solution To the Problemmentioning
confidence: 99%
See 1 more Smart Citation
“…Equation (19) corresponds to the least squares solution of the problem with Tikhonov regularization. 22,33 The right inverse is chosen because it is more efficient computationally for an underdetermined problem like the one addressed here ðL > MÞ, given the dimensions of the product G Although the ' 2 -norm solution is chosen in this work, there are alternative solutions, such as the ' 1 -norm, 14 that promote sparse solutions, i.e., few non-zero coefficients, implicitly acting as a regularization penalty.…”
Section: B Regularized Solution To the Problemmentioning
confidence: 99%
“…10,11 Spherical microphone arrays are widely used for sound source localization, [12][13][14] sound field reproduction-to capture sound fields that can be reproduced with an array of loudspeakers, [15][16][17][18] and sound field analysis and reconstruction. [19][20][21][22][23][24][25][26] The use of rigid spherical microphone arrays for reconstructing sound fields has been the subject of several studies, [20][21][22][23][24] which employ a spherical harmonic expansion to provide a full representation of the sound field (sound pressure, particle velocity, and sound intensity). The expansion is used to extrapolate the sound field to a different radius than measured, thus reconstructing the sound field over a three-dimensional space about the array, i.e., predicting the sound field elsewhere than measured.…”
Section: Introductionmentioning
confidence: 99%
“…Due to their geometry and directional properties, spherical arrays are commonly used in these problems to localize sound sources, [1][2][3][4][5] reconstruct the sound field near a source to examine how it radiates sound, [6][7][8][9][10][11] or capture spatial features of a sound field for its reproduction with a loudspeaker array. 12 The existing methods used for these problems typically rely on solving an underdetermined system of linear equations to obtain the amplitude of the waves that impinge on the array, or alternatively, to obtain the coefficients of a wave expansion used to represent the data captured in the measurement.…”
Section: Introductionmentioning
confidence: 99%
“…2 The second subcategory finds a set of coefficients to the truncated expansion by fitting the model to the measured data, e.g., by minimization of the difference between the measured sound pressure and the predicted sound pressure at the microphone positions in a least squares sense. [3][4][5][6][7] The latter approach does not rely on the orthogonality of the wave functions, and hence the array does not need to be of spherical shape.…”
Section: Introductionmentioning
confidence: 99%