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Cyclostationary spectral analysis for the measurement and prediction of wind turbine swishing noise

机译：循环平稳频谱分析法在风轮机杂音测量和预测中的应用

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This paper introduces, cyclostationary spectral analysis as a new approach to analyzing and predicting the aerodynamic noise generated by wind turbines. This method is able to reveal new insights into the periodic character of the noise signal and is therefore ideally suited to the study of wind turbine noise. A new formulation is presented for the time variation of the noise spectrum due to wind turbines thereby providing insight into the character of the periodic variation in noise referred to as 'swishing'. The character and mechanism of swishing noise is analyzed in detail. Cyclostationary analysis is applied to noise data obtained on a 1.5 MW wind turbine to predict the time variation of the auto correlation function and spectral distribution (Wigner-Ville representation). Comparisons of the predictions with measurements are in good qualitative agreement. A swishing index is proposed to quantify the swishing sound of wind turbine noise.
机译：本文介绍了循环平稳频谱分析作为分析和预测风力涡轮机产生的空气动力噪声的一种新方法。这种方法能够揭示有关噪声信号周期性特征的新见解，因此非常适合研究风力涡轮机噪声。针对由风力涡轮机引起的噪声频谱的时间变化，提出了一种新的公式，从而提供了对噪声周期性变化（称为“摆动”）特征的深入了解。详细分析了产生噪声的特性和机理。将循环平稳分析应用于在1.5 MW风力涡轮机上获得的噪声数据，以预测自动相关函数和频谱分布（Wigner-Ville表示）的时间变化。预测值与测量值的比较在质量上吻合良好。提出了扰动指标以量化风力涡轮机噪声的扰动声音。

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