Comparison of anomaly detection techniques for wind turbine gearbox SCADA data
| Main Authors: | McKinnon, Conor, Carroll, James, McDonald, Alasdair, Koukoura, Sofia, Soraghan, Connaill |
|---|---|
| Format: | info Proceeding Journal |
| Terbitan: |
, 2021
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| Online Access: |
https://zenodo.org/record/4550706 |
Daftar Isi:
- 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).