Use of SCADA Data for Failure Detection in Wind Turbines

Kyusung Kim, Girija Parthasarathy, Onder Uluyol, Wendy Foslien, Shuangwen Sheng, Paul Fleming

Research output: Contribution to conferencePaperpeer-review

110 Scopus Citations


High operations and maintenance costs for wind turbines reduce their overall cost effectiveness. One of the biggest drivers of maintenance cost is unscheduled maintenance due to unexpected failures. Continuous monitoring of wind turbine health using automated failure detection algorithms can improve turbine reliability and reduce maintenance costs by detecting failures before they reach a catastrophic stage and by eliminating unnecessary scheduled maintenance. A SCADA (Supervisory Control and Data Acquisition System) -data based condition monitoring system uses data already collected at the wind turbine controller. It is a cost-effective way to monitor wind turbines for early warning of failures and performance issues. In this paper, we describe our exploration of existing wind turbine SCADA data for development of fault detection and diagnostic techniques for wind turbines. We used a number of measurements to develop anomaly detection algorithms and investigated classification techniques using clustering algorithms and principal components analysis for capturing fault signatures. Anomalous signatures due to a reported gearbox failure are identified from a set of original measurements including rotor speeds and produced power.

Original languageAmerican English
Number of pages9
StatePublished - 2011
EventASME 2011 5th International Conference on Energy Sustainability, ES 2011 - Washington, DC, United States
Duration: 7 Aug 201110 Aug 2011


ConferenceASME 2011 5th International Conference on Energy Sustainability, ES 2011
Country/TerritoryUnited States
CityWashington, DC

NREL Publication Number

  • NREL/CP-5000-51653


  • gearbox failure
  • supervisory control and data acquisition
  • wind turbine condition monitoring
  • wind turbine gearbox


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