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Virtual Rotating Array for Near-Field Localization of Rotating Sound Sources.

  • Published In: Journal of Theoretical & Computational Acoustics, 2024, v. 32, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Feng, Jianixong; Liu, Yangfan; Li, Kai Ming 3 of 3

Abstract

In this study, a more efficient time domain (TD) virtual rotating array (VRA) method is proposed that employs a zeroth-order interpolation scheme. The interpolation of sound fields in the receiver plane using only the nearest microphone at each time step improves the efficiency of the entire process. Additionally, the VRA method is demonstrated to function well with near-field acoustic holography for localizing rotating sound sources. The proposed methods are numerically and experimentally validated. The zeroth-order interpolation scheme is compared with linear, barycentric, and radial basis function schemes using either a circular array or an arbitrary array. The holographic reconstructions are compared for selected one-third octave band center frequencies. Compressive sensing-based holography is used for increasing the resolution of the numerical simulations at low frequencies. The source strength is calculated by integrating the holographic spectra in the source plane. A comparison of the predicted source strengths and locations suggests that the zeroth-order scheme yields a more accurate solution than higher-order schemes. The proposed zeroth-order scheme and the source reconstruction using VRA signals have the potential to visualize sound fields produced by compact rotating structures. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Theoretical & Computational Acoustics. 2024/03, Vol. 32, Issue 1, p1
  • Document Type:Article
  • Subject Area:Mathematics
  • Publication Date:2024
  • ISSN:2591-7285
  • DOI:10.1142/S2591728523400078
  • Accession Number:176387550
  • Copyright Statement:Copyright of Journal of Theoretical & Computational Acoustics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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