Research Article
Health Status Assessment for Wind Turbine with Recurrent Neural Networks
Table 7
Performance criterions of the traditional LSTM neural network for wind turbine 2.
| SCADA variables | RMSE | MAE | BIAS | SDE |
| Generator speed | 0.296 | 0.173 | -0.147 | 0.256 | Generator temperature | 0.056 | 0.037 | 0.015 | 0.056 | Generator cooling air temperature | 0.076 | 0.045 | 0.13 | 0.075 | Generator bearing temperature | 0.057 | 0.043 | 0.019 | 0.054 | Gearbox temperature | 0.035 | 0.028 | 0.017 | 0.031 | Gearbox bearing temperature | 0.066 | 0.052 | -0.02 | 0.063 | Rotor speed | 0.3 | 0.178 | -0.151 | 0.242 | Battery box temperature | 0.105 | 0.1 | 0.1 | 0.033 | Hydraulic pressure | 0.087 | 0.046 | -0.015 | 0.085 | Shaft bearing temperature | 0.11 | 0.11 | -0.11 | 0.026 | Top box temperature | 0.03 | 0.025 | -0.005 | 0.03 |
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