Research Article
DC-NNMN: Across Components Fault Diagnosis Based on Deep Few-Shot Learning
| Layer | Symbol | Operate | Parameter size |
| 1 | Input | Input samples | 864 |
| | | Convolution | 3 × 1 × 64 | 2 | Conv1 | Batch normalization | — | | | Leaky ReLU | Leaky |
| 3 | Pool1 | Max pooling | 2 × 1 |
| | | Convolution | 3 × 1 × 64 | 4 | Conv2 | Batch normalization | — | | | Leaky ReLU | Leaky |
| 5 | Pool2 | Max pooling | 2 × 1 |
| | | Convolution | 3 × 1 × 64 | 6 | Conv3 | Batch normalization | — | | | Leaky ReLU | Leaky |
| | | Convolution | 3 × 1 × 64 | 7 | Conv4 | Batch normalization | — | | | Leaky ReLU | Leaky |
| 8 | Output | Output features | 216 × 1 × 64 |
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