Research Article
Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition
Table 9
Bearing fault diagnosis results obtained by OFS-MMC-SVM.
| Dimension size | DTCWPT | WPT | Case 1 testing accuracy (%) | Case 2 testing accuracy (%) | Case 3 testing accuracy (%) | Case 4 testing accuracy (%) | Case 1 testing accuracy (%) | Case 2 testing accuracy (%) | Case 3 testing accuracy (%) | Case 4 testing accuracy (%) |
| 5 | 92.71 | 79.79 | 96.46 | 71.67 | 95.00 | 75.00 | 96.67 | 62.71 | 7 | 97.29 | 82.92 | 96.25 | 80.42 | 95.21 | 72.08 | 99.17 | 80.21 | 9 | 98.75 | 86.04 | 95.42 | 82.08 | 96.25 | 72.50 | 99.17 | 82.71 | 11 | 99.17 | 86.46 | 97.08 | 85.21 | 96.25 | 72.50 | 98.96 | 83.54 |
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