Omni-directional equivalent source sound source identification method based on solid ball array

Abstract

The invention discloses an omni-directional equivalent source sound source identification method based on a solid ball array. The method includes the steps that 1, sound field radiation total sound pressure measured by the solid ball array is acquired; 2, the equivalent source intensity q is calculated on the basis of an iterative weighting algorithm, wherein the solving formula is shown in the description, in the formula, W refers to a weighting matrix which is a reversible matrix with non-zero diagonal elements, and lambda is a regularization parameter; S3, the sound pressure at any positionis reconstructed. The method has the advantages that the sound source positioning precision and the sound field rebuilding performance are excellent at medium and low frequency and large measuring distances.

Description

technical field [0001] The invention belongs to the technical field of sound field identification, and in particular relates to a sound source identification method of a spherical equivalent source of a solid sphere array. Background technique [0002] The Spherical Equivalent Source Method (S-ESM) based on solid sphere array is a new algorithm for omnidirectional sound field reconstruction and sound source identification. The traditional S-ESM is solved by standard Tikhonov regularization technology. However, due to the limitation of Nyquist sampling theorem, the limitation of Tikhonov regularization and the instability of regularization parameters, its reconstruction accuracy can only be achieved at medium and low frequencies and small measurement distances. accept. [0003] The spherical array equivalent source (SDI-based S-ESM, referred to as SDI) based on the fastest descent iteration (Steepest Descent Iteration, SDI) has achieved better medium and high frequency recon...

AI Technical Summary

Problems solved by technology

The traditional S-ESM is solved by standard Tikhonov regularization technology. However, due to the limitation of Nyquist sampling theorem, the limitation of Tikhonov regularization and the instability of regularization parameters, its reconstruction accuracy can only be achieved at medium and low frequencies and small measurement distances. accept

[0003] The spherical array equivalent source (SDI-based S-ESM, referred to as SDI) based on the fastest descent iteration (Steepest Descent Iteration, SDI) has achieved better medium and high frequency reconstruction performance, and broadened the S-ESM in sound source identification. Applicable distance in the field, but limited by the inherent defects of the fastest descent iterative solution, SDI has poor sound field reconstruction and sound source identification performance at low frequencies and large measurement distances

Images