Research Article
A Novel Method for Remaining Useful Life Prediction of Roller Bearings Involving the Discrepancy and Similarity of Degradation Trajectories
Table 2
Specific setting parameters of the convolutional encoder.
| Layer | Parameters | Output size | Activation function |
| Input layer | — | 128 × 128 × 3 | — | Convolutional layer 1 | 15 kernels, size: 3 × 3 | 128 × 128 × 15 | ReLU | Pooling layer 1 | Size: 4 × 4, stride: 4 × 4 | 32 × 32 × 15 | — | Convolutional layer 2 | 15 kernels, size: 3 × 3 | 32 × 32 × 15 | ReLU | Pooling layer 2 | Size: 4 × 4, stride: 4 × 4 | 8 × 8 × 15 | — | Convolutional layer 3 | 15 kernels, size: 3 × 3 | 8 × 8 × 15 | ReLU | Pooling layer 3 | Size: 2 × 2, stride: 2 × 2 | 4 × 4 × 15 | — | Fully connected layer | 240 neurons | 1 × 240 | — |
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