Articles | Volume 11, issue 5
https://doi.org/10.5194/wes-11-1771-2026
https://doi.org/10.5194/wes-11-1771-2026
Research article
 | 
19 May 2026
Research article |  | 19 May 2026

A two-stage framework for identifying and characterizing wind turbine noise data and its validation by listening tests

Susanne Könecke, Clemens Jonscher, Tobias Bohne, and Raimund Rolfes

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Latest update: 02 Nov 2026
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Short summary
This paper presents a framework to identify wind turbine noise in long-term field measurements. By combining statistical criteria, turbine operating data, and physics-based signal analysis, periods dominated by wind turbine noise and its key components are detected. The framework is validated using a structured listening test and applied to a 1-month dataset. The framework, listening-test platform, and anonymized audio data are publicly available to support further research.
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