Wind Energy Science
Wind Energy Science
WES
Articles | Volume 8, issue 4
Articles | Volume 8, issue 4
https://doi.org/10.5194/wes-8-557-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-557-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 8, issue 4
Research article
 | 
14 Apr 2023
Research article |  | 14 Apr 2023

Anomaly-based fault detection in wind turbine main bearings

Lorena Campoverde-Vilela, María del Cisne Feijóo, Yolanda Vidal, José Sampietro, and Christian Tutivén

Viewed

Total article views: 5,661 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,466 1,092 103 5,661 101 152
  • HTML: 4,466
  • PDF: 1,092
  • XML: 103
  • Total: 5,661
  • BibTeX: 101
  • EndNote: 152
Views and downloads (calculated since 01 Feb 2023)
Cumulative views and downloads (calculated since 01 Feb 2023)

Viewed (geographical distribution)

Total article views: 5,661 (including HTML, PDF, and XML) Thereof 5,524 with geography defined and 137 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 04 May 2026
Download
Short summary
In order to provide early warnings of faults in the main bearing, a fault detection system is developed by applying an anomaly detector based on principal component analysis. Without the need to obtain the fault history or install additional equipment or sensors that would require a larger investment, this model is constructed using only healthy supervisory control and data acquisition (SCADA) data. The results obtained enable failure detection even months before the fatal breakdown takes place.
Read more
Share
Altmetrics
Final-revised paper
Preprint