Abstract
This analysis looks at the use of anomaly detection to assess the condition of wind turbine gearboxes based on data from a number of operational turbines. A comparison is made between various methods of anomaly detection, these being one class support vector machine (OCSVM), random forests, and nonlinear autoregressive neural networks with exogenous inputs (NARX).
Original language | English |
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Number of pages | 1 |
Publication status | Published - 17 Jun 2019 |
Event | Wind Energy Science Conference 2019 - University College Cork, Cork, Ireland Duration: 17 Jun 2019 → 20 Jun 2019 Conference number: 2019 https://www.wesc2019.org/ |
Conference
Conference | Wind Energy Science Conference 2019 |
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Abbreviated title | WESC |
Country/Territory | Ireland |
City | Cork |
Period | 17/06/19 → 20/06/19 |
Internet address |
Keywords
- anomaly detection
- operations and maintenance (O&M)
- wind turbines
- one class support vector machine
- neural networks with exogenous inputs
- wind energy