Research Article
Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings
Table 18
Prediction accuracies for 32
32 image inputs.
| Model | Spectrogram | Scalogram | HHT |
| MLP flat | 92.7% | 83.6% | 59.6% | LSVM flat | 88.6% | 80.8% | 59.7% | SVM flat | 97.3% | 89.3% | 72.5% | MLP PCA | 89.4% | 94.7% | 76.0% | LSVM PCA | 77.9% | 69.3% | 59.7% | SVM PCA | 74.4% | 90.0% | 80.0% | Architecture 2 | 95.9% | 92.6% | 78.0% | Architecture 1 | 98.4% | 99.2% | 88.9% | Proposed CNN architecture | 98.1% | 98.8% | 86.5% |
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