Research Article
Discrete Cosine Transformation and Temporal Adjacent Convolutional Neural Network-Based Remaining Useful Life Estimation of Bearings
Table 5
Time consuming in model training (unit: s).
| Input size/H × W × C | TFR-TACNN | DCT-TACNN |
| 500 × 500 × 2 | Overflow | 598 (pruned 26.5%) | 250 × 250 × 2 | 1021 (pruned 5.9%) | 266 (pruned 20.9%) | 100 × 100 × 2 | 452 (pruned 10.0%) | 72 (pruned 17.5%) | 50 × 50 × 2 | 231 (pruned 9.5%) | 40 (pruned 24.0%) |
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