Research Article
Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition
Table 8
Bearing fault diagnosis results obtained by OFS-LFDA-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 | 98.75 | 81.67 | 94.79 | 72.71 | 81.46 | 54.79 | 86.88 | 52.08 | 7 | 99.58 | 86.45 | 95.83 | 73.33 | 82.71 | 55.42 | 92.08 | 53.75 | 9 | 99.58 | 86.67 | 96.46 | 73.54 | 82.92 | 56.25 | 92.92 | 53.75 | 11 | 99.79 | 86.88 | 96.46 | 73.54 | 83.13 | 56.25 | 92.92 | 53.75 |
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