Table 5 F1-score performance comparison of different models in CWRU dataset under different SNRs (%).
From: Attention activation network for bearing fault diagnosis under various noise environments
SNR (dB) | \(-\)9 | \(-\)6 | \(-\)3 | 0 | 3 | 6 | 9 | |
|---|---|---|---|---|---|---|---|---|
Model | Noise type | |||||||
MLSCA-CW (two locations) | Gauss | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 |
Laplace | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
Violet | 87.802 | 90.130 | 93.052 | 95.452 | 100.000 | 100.000 | 100.000 | |
Brown | 98.942 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
Mixed | 94.320 | 97.333 | 99.460 | 100.000 | 100.000 | 100.000 | 100.000 | |
MLSCA-CW (single ___location) | Gauss | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 |
Laplace | 98.401 | 99.349 | 99.507 | 100.000 | 100.000 | 100.000 | 100.000 | |
Violet | 88.815 | 89.326 | 89.665 | 92.078 | 92.563 | 98.985 | 100.000 | |
Brown | 99.423 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
Mixed | 88.649 | 95.360 | 99.460 | 99.460 | 100.000 | 100.000 | 100.000 | |
LR | Gauss | 38.477 | 39.334 | 50.944 | 56.203 | 64.422 | 74.491 | 77.103 |
Laplace | 32.712 | 37.082 | 53.722 | 60.418 | 63.232 | 65.506 | 67.829 | |
Violet | 41.206 | 41.737 | 43.645 | 45.199 | 46.185 | 52.642 | 58.449 | |
Brown | 13.939 | 15.643 | 19.439 | 20.339 | 24.304 | 28.845 | 39.236 | |
Mixed | 40.637 | 42.835 | 48.288 | 50.714 | 54.749 | 55.324 | 57.463 | |
MC-CNN | Gauss | 96.826 | 97.784 | 99.500 | 100.000 | 100.000 | 100.000 | 100.000 |
Laplace | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
Violet | 72.880 | 76.414 | 92.008 | 97.726 | 100.000 | 100.000 | 100.000 | |
Brown | 19.111 | 28.976 | 99.400 | 100.000 | 100.000 | 100.000 | 100.000 | |
Mixed | 79.630 | 84.524 | 99.276 | 100.000 | 100.000 | 100.000 | 100.000 | |
WDCNN | Gauss | 52.476 | 65.848 | 90.640 | 99.418 | 99.418 | 100.000 | 100.000 |
Laplace | 93.582 | 96.307 | 97.047 | 97.499 | 98.780 | 100.000 | 100.000 | |
Violet | 73.759 | 75.463 | 76.335 | 80.832 | 89.444 | 96.454 | 100.000 | |
Brown | 85.080 | 86.575 | 91.957 | 99.235 | 100.000 | 100.000 | 100.000 | |
Mixed | 76.725 | 79.217 | 88.710 | 99.525 | 100.000 | 100.000 | 100.000 | |
Multiscale inner product | Gauss | 90.388 | 97.898 | 98.439 | 99.465 | 100.000 | 100.000 | 100.000 |
Laplace | 85.418 | 93.438 | 99.438 | 100.000 | 100.000 | 100.000 | 100.000 | |
Violet | 81.336 | 84.192 | 86.129 | 87.263 | 89.512 | 95.903 | 100.000 | |
Brown | 99.468 | 99.468 | 99.496 | 100.000 | 100.000 | 100.000 | 100.000 | |
Mixed | 91.087 | 93.436 | 97.350 | 98.735 | 99.418 | 100.000 | 100.000 | |
SANet | Gauss | 90.528 | 91.841 | 92.751 | 93.612 | 100.000 | 100.000 | 100.000 |
Laplace | 97.585 | 99.463 | 99.490 | 99.496 | 100.000 | 100.000 | 100.000 | |
Violet | 57.685 | 64.359 | 61.165 | 78.834 | 81.678 | 95.925 | 100.000 | |
Brown | 13.939 | 37.957 | 42.133 | 60.103 | 68.290 | 68.908 | 69.014 | |
Mixed | 57.704 | 68.707 | 79.048 | 87.701 | 96.641 | 99.051 | 100.000 | |
QCNN | Gauss | 99.463 | 99.463 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 |
Laplace | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | 100.000 | |
Violet | 77.840 | 83.911 | 88.613 | 91.222 | 94.186 | 100.000 | 100.000 | |
Brown | 89.551 | 89.727 | 98.866 | 99.490 | 99.496 | 100.000 | 100.000 | |
Mixed | 86.803 | 89.614 | 90.267 | 97.956 | 100.000 | 100.000 | 100.000 | |
