Research Article
Rotating Machinery Fault Diagnosis for Imbalanced Data Based on Fast Clustering Algorithm and Support Vector Machine
Table 3
Classification accuracy comparisons of fault diagnosis model and other models.
| Proportion of the data set | 10 : 150 | 15 : 150 | 40 : 150 | 50 : 150 | 80 : 150 | 100 : 150 |
| Fault diagnosis model | 85.33% | 81.67% | 85.00% | 87.67% | 89.33% | 88.67% | FCA + BP | 74.00% | 76.67% | 80.67% | 83.33% | 81.33% | 85.33% | FCA + RBF | 73.67% | 73.00% | 74.67% | 75.67% | 80.33% | 88.33% | RU + SVM | 79.67% | 78.67% | 80.00% | 82.00% | 84.00% | 86.00% | RU + BP | 71.00% | 70.33% | 82.33% | 86.67% | 87.33% | 87.33% | RU + RBF | 76.33% | 75.67% | 79.33% | 78.67% | 85.33% | 85.00% | SMOTE + SVM | 75.67% | 77.67% | 78.67% | 82.00% | 83.33% | 85.67% | SMOTE + BP | 72.00% | 79.67% | 82.33% | 84.33% | 85.33% | 87.33% | SMOTE + RBF | 76.00% | 78.67% | 78.67% | 80.00% | 83.67% | 82.33% | SVM | 68.00% | 71.67% | 76.33% | 79.00% | 83.00% | 84.67% | BP | 66.00% | 70.67% | 81.00% | 83.00% | 82.00% | 84.33% | RBF | 53.67% | 65.33% | 78.00% | 81.67% | 82.67% | 84.67% |
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