Research Article
Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition
Table 7
Bearing fault diagnosis results obtained by OFS-LDA-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 | 96.25 | 80.62 | 95.00 | 82.08 | 92.50 | 77.71 | 95.00 | 76.88 | 7 | 98.13 | 86.25 | 95.83 | 88.33 | 94.58 | 80.42 | 97.71 | 71.67 | 9 | 98.75 | 86.04 | 96.25 | 88.75 | 95.21 | 80.42 | 97.71 | 76.67 | 11 | 99.17 | 85.83 | 96.46 | 88.54 | 95.63 | 80.21 | 98.13 | 77.08 |
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