Research Article
Aero Engine Gas-Path Fault Diagnose Based on Multimodal Deep Neural Networks
Table 3
Comparison of the performance without and with
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| Dataset | BPNN | CNN | Multimodal results | Without | With |
| Chlor.Conc | 0.991 | 0.993 | 0.999 | 0.999 | Cinc_ECG | 0.958 | 0.996 | 1.00 | 1.00 | Dist.phal.O.C | 0.835 | 0.858 | 0.858 | 0.864 | ECGFivedays | 0.983 | 1.00 | 1.00 | 1.00 | yoga | 0.931 | 0.926 | 0.939 | 0.941 | Type A | 0.9598 | 0.9489 | 0.9621 | 0.9627 | Type B | 0.9818 | 0.9771 | 0.9843 | 0.9864 |
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