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Modal identification of a small-scale ducted fan

机译:模态识别小型管道风扇

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The subject of this paper is the experimental investigation of the noise radiated by a ducted rotating machine. A modal identification approach is used to decompose the radiated sound field into duct modes from acoustic pressure measured by wall-flush mounted microphones. Both azimuthal and radial decompositions are computed by means of an array with optimized microphone arrangement. The optimized array ensures a low condition number of the matrix relating modal coefficients to acoustic pressure over a wide frequency band, up to the second harmonic of the blade passing frequency. Above this frequency the number of cut-on modes is comparable to the number of microphones and the modal matrix suffers from ill-conditioning. A regularization procedure is then introduced to increase the high-frequency limit of the method. Results are presented for both tonal and broadband components of the radiated sound field. The difficulty in the broadband regime is that pressure fluctuations measured by in-duct microphones are strongly affected by hydrodynamic noise associated to the turbulent boundary layer (TBL). A technique to suppress the TBL related noise is thus applied prior to the modal identification, its interest is shown on experimental data from an academic test bench.
机译:本文的主题是管道旋转机器辐射的噪声的实验研究。模态识别方法用于将辐射声场分解为由壁式上安装麦克风测量的声压来分解到管道模式。借助于具有优化麦克风布置的阵列来计算方位角和径向分解。优化阵列确保矩阵的低条件数与宽频带上的模态系数相关的模数系数相关,直到叶片通过频率的第二谐波。在此频率之上,切割模式的数量与麦克风的数量相当,并且模态矩阵遭受不良状态。然后引入正则化程序以增加方法的高频极限。辐射声场的色调和宽带部件呈现出结果。宽带方案中的难度是通过管道麦克风测量的压力波动受到与湍流边界层(TBL)相关的流体动力噪声的强烈影响。因此,在模态识别之前应用了抑制TBL相关噪声的技术,其兴趣在学术测试台上显示了实验数据。

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