Early fault detection in the main bearing of wind turbines based on Gated Recurrent Unit (GRU) neural networks and SCADA data
Cita com:
hdl:2117/371579
Tipus de documentArticle
Data publicació2022
EditorInstitute of Electrical and Electronics Engineers (IEEE)
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 4.0 Internacional
Abstract
Failures in the main bearings of wind turbines are critical in terms of downtime and replacement cost. Early diagnosis of their faults would lower the levelized cost of wind energy. Thus, this work discusses a gated recurrent unit (GRU) neural network, which detects faults in the main bearing some months ahead (when the event that initiates/develops the failure releases heat) the actual fatal fault materializes. GRUs feature internal gates that govern information flow and are utilized in this study for their capacity to understand whether data in a time series is crucial enough to preserve or forget. It is noteworthy that the proposed methodology only requires healthy supervisory control and data acquisition (SCADA) data. Thus, it can be deployed to old wind parks (nearing the end of their lifespan) where specific high-frequency condition monitoring sensors are not installed and to new wind parks where faulty historical data do not exist yet. The strategy is trained, validated, and finally tested using SCADA data from an in-production wind park composed of nine wind turbines.
Descripció
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CitacióEncalada-Dávila, Á. [et al.]. Early fault detection in the main bearing of wind turbines based on Gated Recurrent Unit (GRU) neural networks and SCADA data. "IEEE-ASME transactions on mechatronics", 2022, p. 1-11.
ISSN1083-4435
Versió de l'editorhttps://ieeexplore.ieee.org/document/9823312
Fitxers | Descripció | Mida | Format | Visualitza |
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FINAL VERSION.pdf | Accepted version | 9,761Mb | Visualitza/Obre | |
FINAL VERSION.pdf | Accepted version | 9,761Mb | Visualitza/Obre | |
FINAL VERSION.pdf | Accepted version | 9,761Mb | Visualitza/Obre |
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
FINAL VERSION.pdf | Accepted version | 9,761Mb | Visualitza/Obre |