Research Article
Classification of Fault Severity in Induction Machine Systems Based on Temporal Convolutions and Recurrent Networks
Table 2
Accuracy, precision, recall, and F1 score measurement of 12 classes for the LSTM-FCN.
| | | Runb (p.u.) | Class | Precision | Recall | F1 score |
| | Healthy | 0 | A1 | 1.00 | 1.00 | 1.00 | | A2 | 0.98 | 1.00 | 0.99 | | A3 | 098 | 1.00 | 0.99 |
| | Faulty | 0.003 | A4 | 1.00 | 1.00 | 1.00 | | A5 | 0.99 | 0.98 | 0.98 | | A6 | 0.97 | 0.99 | 0.98 | | 0.031 | A7 | 1.00 | 1.00 | 1.00 | | A8 | 1.00 | 0.98 | 0.99 | | A9 | 0.96 | 0.98 | 0.99 | | 0.093 | A10 | 1.00 | 1.00 | 1.00 | | A11 | 1.00 | 1.00 | 1.00 | | A12 | 1.00 | 0.95 | 0.97 |
| | Accuracy | 98.92% |
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