Research Article
Fault Diagnosis with Evolving Fuzzy Classifier Based on Clustering Algorithm and Drift Detection
Table 2
Fault detection performance.
| Scenario | Proposed | Lemos et al. [10] | POD (%) | POFA (%) | ACC (%) | POD (%) | POFA (%) | ACC (%) |
| 3 faults | 99.85 | 0.00 | 99.89 | 99.79 | 0.00 | 99.85 | 5 faults | 99.68 | 0.00 | 99.72 | 98.39 | 0.00 | 98.66 | 7 faults | 99.79 | 0.00 | 99.89 | 98.50 | 0.00 | 98.68 | 9 faults | 99.82 | 0.03 | 99.93 | 99.77 | 0.00 | 99.79 | 11 faults | 99.33 | 0.29 | 99.32 | 93.73 | 0.00 | 94.26 |
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