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Séminaire ISTerre
Machine-learning driven signal characterization of seismic wind turbine emissions
mardi 20 février 2024 - 11h00
Marie Gärtner - MsC student from Karlsruhe---
Wind turbine (WT) emissions significantly affect the sensitivity and resolution of sensitive measurement instruments. Looking at the signals and their spectrograms, distinct signals corresponding to the eigenmodes of the WTs tower and blades, as well as the multiples of the blade passing frequency can be observed. The observed ground motion patterns are influenced not only by the WT's rotation rate but also by factors such as meteorological conditions. Utilizing machine-learning tools, the goal of my work is to enhance the grouping of seismic WT emissions, identify patterns associated with the WTs and their operation, and establish links between signal patterns and meteorological effects or other signals.
Equipe organisatrice : Ondes et structures
Amphithéâtre Killian, Maison des Géosciences, 38400 Saint Martin d'Hères