doi:10.1088/1742-6596/926/1/012009engGonzález, E.Stephen, B.Infield, D.Melero, J.J.On the use of high-frequency SCADA data for improved wind turbine performance monitoringART-2017-102527SCADA-based condition monitoring of wind turbines facilitates the move from costly corrective repairs towards more proactive maintenance strategies. In this work, we advocate the use of high-frequency SCADA data and quantile regression to build a cost effective performance monitoring tool. The benefits of the approach are demonstrated through the comparison between state-of-the-art deterministic power curve modelling techniques and the suggested probabilistic model. Detection capabilities are compared for low and high-frequency SCADA data, providing evidence for monitoring at higher resolutions. Operational data from healthy and faulty turbines are used to provide a practical example of usage with the proposed tool, effectively achieving the detection of an incipient gearbox malfunction at a time horizon of more than one month prior to the actual occurrence of the failure.2017http://zaguan.unizar.es/record/6342310.1088/1742-6596/926/1/012009http://zaguan.unizar.es/record/63423oai:zaguan.unizar.es:63423This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 642108-AWESOMEinfo:eu-repo/grantAgreement/EC/H2020/642108/EU/Advanced Wind Energy Systems Operation and Maintenance Expertise/AWESOMEJournal of physics. Conference series 926 (2017), 012009 [14 pp]byhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccess