scholarly journals Optimization of secondary source configuration in enclosure using plane wave decomposition

2021 ◽  
Vol 39 (4) ◽  
pp. 794-800
Author(s):  
Jian Xu ◽  
Kean Chen ◽  
Lei Wang ◽  
Yazhou Zhang
Keyword(s):  
Potential Energy ◽  
Plane Wave ◽  
Noise Reduction ◽  
Prior Knowledge ◽  
Optimization Method ◽  
Secondary Source ◽  
Spatial Region ◽  
Plane Wave Decomposition ◽  
Wave Decomposition ◽  
Field Plane

The optimization of secondary source configuration for an active noise control (ANC) system in its enclosed space generally focuses on noise reduction requirements at discrete points only. This may lead to the poor noise reduction performance in the whole spatial region, and it is necessary to know the information on error sensor positions in advance. To address this problem, a cost function for spatial-region-oriented noise reduction is proposed. The plane wave decomposition of the enclosed sound field is used to obtain the primary field plane waves and the unit secondary field plane wave of each candidate secondary source as the prior knowledge for configuration optimization, so as to formulate a wave-domain ANC cost function. The optimization method adopts the simulated annealing search. Taking a rigid-walled rectangular cavity as an example, the optimization method is firstly compared with two space-domain methods by using analytic values of the wave-domain prior knowledge. The comparison results show that the better reduction of spatial acoustic potential energy can be achieved independent of the error sensor configuration information. Then the estimated values of the wave-domain prior knowledge through measuring randomly distributed microphones are used to optimize the configuration of the ANC system. The optimization results suggest that the noise reduction of spatial acoustic potential energy of the optimized configuration can be better than that of the space-domain method, but the microphone positions have a great influence on the noise reduction performance.

A fast algorithm for plane-wave decomposition

1985 ◽  
Author(s):  
Julian Cabrera ◽  
Shlomo Levy ◽  
Kerry Stinson
Keyword(s):  
Plane Wave ◽  
Fast Algorithm ◽  
Plane Wave Decomposition ◽  
Wave Decomposition

scholarly journals Denoising Directional Room Impulse Responses with Spatially Anisotropic Late Reverberation Tails

2020 ◽  
Vol 10 (3) ◽  
pp. 1033 ◽  
Author(s):  
Pierre Massé ◽  
Thibaut Carpentier ◽  
Olivier Warusfel ◽  
Markus Noisternig
Keyword(s):  
Plane Wave ◽  
Gaussian Noise ◽  
Three Dimensional ◽  
Microphone Arrays ◽  
Impulse Responses ◽  
Noise Floor ◽  
Surround Sound ◽  
Plane Wave Decomposition ◽  
Spherical Microphone Arrays ◽  
Wave Decomposition

Directional room impulse responses (DRIR) measured with spherical microphone arrays (SMA) enable the reproduction of room reverberation effects on three-dimensional surround-sound systems (e.g., Higher-Order Ambisonics) through multichannel convolution. However, such measurements inevitably contain a nondecaying noise floor that may produce an audible “infinite reverberation effect” upon convolution. If the late reverberation tail can be considered a diffuse field before reaching the noise floor, the latter may be removed and replaced with an extension of the exponentially-decaying tail synthesized as a zero-mean Gaussian noise. This has previously been shown to preserve the diffuse-field properties of the late reverberation tail when performed in the spherical harmonic domain (SHD). In this paper, we show that in the case of highly anisotropic yet incoherent late fields, the spatial symmetry of the spherical harmonics is not conducive to preserving the energy distribution of the reverberation tail. To remedy this, we propose denoising in an optimized spatial domain obtained by plane-wave decomposition (PWD), and demonstrate that this method equally preserves the incoherence of the late reverberation field.

On plane‐wave decomposition: Alias removal

Geophysics ◽  
1989 ◽  
Vol 54 (10) ◽  
pp. 1339-1343 ◽  
Author(s):  
S. C. Singh ◽  
G. F. West ◽  
C. H. Chapman
Keyword(s):  
Plane Wave ◽  
Seismic Data ◽  
P Wave ◽  
S Wave ◽  
Plane Wave Decomposition ◽  
Time Migration ◽  
Time Distance ◽  
P Domain ◽  
Wave Decomposition ◽  
Rapid Modeling

The delay‐time (τ‐p) parameterization, which is also known as the plane‐wave decomposition (PWD) of seismic data, has several advantages over the more traditional time‐distance (t‐x) representation (Schultz and Claerbout, 1978). Plane‐wave seismograms in the (τ, p) domain can be used for obtaining subsurface elastic properties (P‐wave and S‐wave velocities and density as functions of depth) from inversion of the observed oblique‐incidence seismic data (e.g., Yagle and Levy, 1985; Carazzone, 1986; Carrion, 1986; Singh et al., 1989). Treitel et al. (1982) performed time migration of plane‐wave seismograms. Diebold and Stoffa (1981) used plane‐wave seismograms to derive a velocity‐depth function. Decomposing seismic data also allows more rapid modeling, since it is faster to compute synthetic seismograms in the (τ, p) than in the (t, x) domain. Unfortunately, the transformation of seismic data from the (t, x) to the (τ, p) domain may produce artifacts, such as those caused by discrete sampling, of the data in space.

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