Sound source identification in a noisy environment based on inverse patch transfer functions with evanescent Green's functions

Xiang, Shang; Jiang, Weikang; Pan, Siwei

doi:10.1016/j.jsv.2015.08.026

Cited by 13 publications

(6 citation statements)

References 36 publications

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“…It is known that the sound wave propagates as an evanescent wave rather than as a propagation wave. So it is more suitable to select the evanescent Green's function instead of the classic Green's function [15], [23]. The evanescent Green's function matches the property of evanescent waves that wave decays in an exponential form with the distance from the sound source.…”

Section: B Neumann Evanescent Green's Functionmentioning

confidence: 99%

“…Forget developed two iPTF methods [14] which use uniform boundary conditions (Neumann) and mixed boundary conditions (Neumann and Dirichlet) respectively. Xiang [15] presented an evanescent Neumann Green's function for a cuboid cavity. The evanescent Neumann Green's function matches the property of evanescent acoustic waves and shows better convergence than the classic Neumann Green's function in which the decay of acoustic waves is not considered.…”

Section: Introductionmentioning

confidence: 99%

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Inverse Patch Transfer Function With Fast Iterative Shrinkage-Thresholding Algorithm as a Tool for Sparse Source Identification

Lou

Huang

et al. 2020

IEEE Access

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Inverse patch transfer functions (iPTF) method is an efficient technique for sound field reconstruction and separation of arbitrarily shaped sound sources in noisy acoustic environments. By applying Neumann boundary condition to a closed virtual cavity surrounding the source, the Helmholtz integral equation is simplified and can be solved with a Green's function satisfying the Neumann boundary condition. However, in the identification of sparsely distributed sources, ghost sources appear in the result solved by using the iPTF method with classic Tikhonov regularization methods and influence the accuracy of identification. In the present work, an evanescent Green's function with fast convergence of calculation is utilized, and a technique that combines the iPTF method and Fast Iterative Shrinkage-Thresholding Algorithm aimed at improving the performance for the identification of sparsely distributed source is proposed. Then double layer measurements, instead of using expensive p-u probes, are employed to acquire the normal velocity of the hologram surface. In numerical simulations, the normal velocities of two antiphased piston sources are well reconstructed with high sparsity while a disturbing source is radiating in the sound field within the frequency band of 50 to 1000 Hz. Finally, an experiment on two baffled loudspeakers has been carried out. The results of simulations and experiments indicate that the proposed technique has obviously improved the accuracy of the iPTF method in the identification of sparsely distributed sources for the frequency band from 50 to 1000 Hz.

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Section: B Neumann Evanescent Green's Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Inverse Patch Transfer Function With Fast Iterative Shrinkage-Thresholding Algorithm as a Tool for Sparse Source Identification

Lou

Huang

et al. 2020

IEEE Access

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“…In order to express the advanced filtering operator of the proposed method more clearly, we give another representation of its filtering algorithm. Substituting formula (13) into formula 14, we can get…”

Section: Theorem 2 the Function ( ) Defined By Formula (8) Is A Kimentioning

confidence: 99%

“…Reference [12] presented a new approach for solving specific classes of inverse source identification problems. Reference [13] used a modified inverse patch transfer function (IPTF) method to reconstruct the normal velocities of the target source in a noisy environment, and [14] used neural network in combination with genetic programming to implement the load identification of electric equipment. Reference [15] proposed the finite element and wavelet-based method for reconstructing the moving force.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Force Identification Problem Based on a Novel Improved Tikhonov Regularization Method

Ren

Wang

Liu

et al. 2019

Mathematical Problems in Engineering

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The main purpose of this paper is to identify the dynamic forces between the conical pick and the coal-seam. According to the theory of time domain method, the dynamic force identification problem of the system is established. The direct problem is described by Green kernel function method. The dynamic force is expressed by a series of functions superposed by impulses, and the dynamic response of the structure is expressed as a convolution integral form between the input dynamic force and the response of Green kernel function. Because of the ill-conditioned characteristics of the structure matrix and the influence of measurement noise in the process of dynamic force identification, it is difficult to deal with this problem by the usual numerical method. In present content, a novel improved Tikhonov regularization method is proposed to solve ill-posed problems. An engineering example shows that the proposed method is effective and can obtain stable approximate solutions to meet the engineering requirements.

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“…However, this technique cannot accurately reconstruct the local sound field. To identify source velocities in complex environments, the inverse patch transfer functions method (iPTF) suitable for three-dimensional structures was proposed [ 11 , 12 , 13 , 14 ]. However, the problem of inversion of the ill-conditioned matrix needs to be solved when this method is used.…”

Section: Introductionmentioning

confidence: 99%

Recovering the Free-Field Acoustic Characteristics of a Vibrating Structure from Bounded Noisy Underwater Environments

Lin

2021

Sensors

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The vibrational behavior of an underwater structure in the free field is different from that in bounded noisy environments because the fluid–structure interaction is strong in the water and the vibration of the structure caused by disturbing fields (the reflections by boundaries and the fields radiated by sources of disturbances) cannot be ignored. The conventional free field recovery (FFR) technique can only be used to eliminate disturbing fields without considering the difference in the vibrational behavior of the structure in the free field and the complex environment. To recover the free-field acoustic characteristics of a structure from bounded noisy underwater environments, a method combining the boundary element method (BEM) with the vibro-acoustic coupling method is presented. First, the pressures on the measurement surface are obtained. Second, the outgoing sound field and the rigid body scattered sound field are calculated by BEM. Then, the vibro-acoustic coupling method is employed to calculate the elastically radiated scattered sound field. Finally, the sound field radiated by the structure in the free field is recovered by subtracting the rigid body scattered sound field and the elastically radiated scattered sound field from the outgoing sound field. The effectiveness of the proposed method is validated by simulation results.

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Sound source identification in a noisy environment based on inverse patch transfer functions with evanescent Green's functions

Cited by 13 publications

References 36 publications

Inverse Patch Transfer Function With Fast Iterative Shrinkage-Thresholding Algorithm as a Tool for Sparse Source Identification

Inverse Patch Transfer Function With Fast Iterative Shrinkage-Thresholding Algorithm as a Tool for Sparse Source Identification

Dynamic Force Identification Problem Based on a Novel Improved Tikhonov Regularization Method

Recovering the Free-Field Acoustic Characteristics of a Vibrating Structure from Bounded Noisy Underwater Environments

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