Articles | Volume 11, issue 6
https://doi.org/10.5194/wes-11-1963-2026
https://doi.org/10.5194/wes-11-1963-2026
Research article
 | 
04 Jun 2026
Research article |  | 04 Jun 2026

Remote diagnostics for power converter faults in wind turbines based on converter control system data

Timo Lichtenstein, Martin Hippenstiel, and Katharina Fischer

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Short summary
Power converter faults in wind turbines often lead to costly downtime and repeated maintenance. We present a practical, explainable, and fully data-driven approach that utilizes high-resolution converter control system records, 1 min operating data, and event logs to predict whether a fault leads to a long or short standstill. By combining engineered features with interpretable feature reduction, we achieve 89 % accuracy and an F1 score of 0.86, providing support for remote decision-making.
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