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A Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) Determined from Phased Microphone Arrays

机译:从相控阵麦克风阵列确定声源映射(DAMAS)的反卷积方法

摘要

Current processing of acoustic array data is burdened with considerable uncertainty. This study reports an original methodology that serves to demystify array results, reduce misinterpretation, and accurately quantify position and strength of acoustic sources. Traditional array results represent noise sources that are convolved with array beamform response functions, which depend on array geometry, size (with respect to source position and distributions), and frequency. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method removes beamforming characteristics from output presentations. A unique linear system of equations accounts for reciprocal influence at different locations over the array survey region. It makes no assumption beyond the traditional processing assumption of statistically independent noise sources. The full rank equations are solved with a new robust iterative method. DAMAS is quantitatively validated using archival data from a variety of prior high-lift airframe component noise studies, including flap edge/cove, trailing edge, leading edge, slat, and calibration sources. Presentations are explicit and straightforward, as the noise radiated from a region of interest is determined by simply summing the mean-squared values over that region. DAMAS can fully replace existing array processing and presentations methodology in most applications. It appears to dramatically increase the value of arrays to the field of experimental acoustics.
机译:当前对声学阵列数据的处理具有很大的不确定性。这项研究报告了一种原始方法,可用于使阵列结果神秘化,减少误解并准确量化声源的位置和强度。传统的阵列结果表示与阵列波束形状响应函数卷积的噪声源,这些函数取决于阵列的几何形状,大小(相对于源位置和分布)和频率。用于声源映射的反卷积方法(DAMAS)方法从输出表示中删除了波束成形特性。独特的方程式线性系统说明了阵列测量区域上不同位置的相互影响。它没有做出超出统计独立噪声源的传统处理假设的假设。用一种新的鲁棒迭代方法求解满秩方程。使用来自各种先前的高升飞机机体噪声研究的档案数据对DAMAS进行了定量验证,这些数据包括襟翼边缘/凹角,后缘,前缘,板条和校准源。呈现方式清晰明了,因为从感兴趣区域辐射的噪声是通过简单地对该区域的均方值求和来确定的。 DAMAS可以在大多数应用中完全替代现有的阵列处理和展示方法。它似乎极大地增加了阵列在实验声学领域的价值。

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