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DOE OSTI · 1768318

Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics

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Abstract

Wind energy is one of the largest sources of renewable energy in the world. To further reduce the operations and maintenance (O&M) costs of wind farms, it is essential to be able to accurately pinpoint the root causes of different failure modes of interest. An example of such a failure mode that is not yet fully understood is white etching cracks (WEC). This can cause the bearing lifetime to be reduced to 5–10% of its design value. Multiple hypotheses are available in literature concerning its cause. To be able to validate or disprove these hypotheses, it is essential to have historic high-frequency measurement data (e.g., load and vibration levels) available. In time, this will allow linking to the history of the turbine operating data with failure data. This paper discusses the dynamic loading on the turbine during certain events (e.g., emergency stops, run-ups, and during normal operating conditions). By combining the number of specific events that each turbine has seen with the severity of each event, it becomes possible to assess which turbines are most likely to show signs of damage.

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BibTeXRIS

Daems, Pieter-Jan, Guo, Yi (ORCID:000000026413947X), Sheng, Shawn (ORCID:0000000301340907), Peeters, C., Guillaume, P., Helsen, J.. 2021-01-11. Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics. https://doi.org/10.1115/gt2020-15312

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