Amplitude modulation (AM) is a characteristic feature of wind farm noise and has the potential to contribute to annoyance and sleep disturbance. Detection, quantification and characterisation of AM is relevant for regulatory bodies that seek to reduce adverse impacts of wind farm noise and for researchers and wind farm developers that aim to understand and account for this phenomenon. We here present an approach to detect and characterise AM in a comprehensive and long-term wind farm noise data set using human scoring. We established benchmark AM characteristics, which are important for validation and calibration of results obtained using automated methods. We further proposed an advanced AM detection method, which has a predictive power close to the practical limit set by human scoring. Human-based approaches should be considered as benchmark methods for characterising and detecting unique noise features.

调幅 (AM) 是风电场噪声的一个特征，有可能导致烦恼和睡眠障碍。AM 的检测、量化和表征与寻求减少风电场噪声不利影响的监管机构以及旨在了解和解释这种现象的研究人员和风电场开发商相关。我们在此提出了一种使用人工评分在综合和长期风电场噪声数据集中检测和表征 AM 的方法。我们建立了基准 AM 特性，这对于验证和校准使用自动化方法获得的结果很重要。我们进一步提出了一种先进的 AM 检测方法，其预测能力接近人类评分设定的实际极限。