Correction: Broadband Airfoil-Noise Source Localization by Microphone Arrays and Modeling of a Swept Free-Tip Blade

G. Yakhina, M. Roger, A. Finez, Valentin Baron, S. Moreau, Justine Giez
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引用次数: 2

Abstract

The present paper describes a post-processing methodology of microphone-array results for accurate source localization and separation. A deconvolution method CIRA is used to extract quantitative spectral results for multiple noise sources identified on a wallmounted, finite-span swept and cambered airfoil tested in an open-jet aeroacoustic facility. This allows understanding the contribution of each source in the noise generation process. The total sound pressure level is reconstructed from the individual spectra of each noise source and extrapolated in the far field to be compared with a single-microphone spectrum. The Bayesian algorithm is used to improve the comparison between reconstructed and experimental spectra as it takes into account the coherent nature of the sources. Remaining discrepancies motivate a re-examination of the assumptions made in the post-processing, aimed at making the spectral characterization of extracted sources more accurate. For this, analytical models of the source mechanisms and of their spanwise correlation are proposed as a tool to define future improvements.
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修正:宽带翼型噪声源定位的麦克风阵列和建模的扫过的自由尖端叶片
本文描述了一种用于精确定位和分离源的麦克风阵列结果的后处理方法。采用反褶积方法CIRA,对在开放式气动声学设备上进行的壁挂式有限跨掠弧面翼型噪声源进行了定量频谱提取。这样就可以了解每个噪声源在噪声产生过程中的作用。总声压级由每个噪声源的单独频谱重建,并在远场外推,以便与单麦克风频谱进行比较。贝叶斯算法考虑了源的相干性,提高了重建光谱与实验光谱的可比性。剩余的差异促使对后处理中所做的假设进行重新检查,目的是使提取的源的光谱特征更准确。为此,提出了源机制的分析模型及其跨度相关性,作为确定未来改进的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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