Research Article
Fault Diagnosis of Rotating Machinery Based on Multisensor Information Fusion Using SVM and Time-Domain Features
Table 5
Diagnostic results of rolling bearing by using different single sensors.
| Sensor |
The best parameter | Diagnostic accuracy (%) | | | Normal | Inner race defect | Outer race defect | Ball defect | All testing samples |
| t
1 | 214.5 | 2ā1.5 | 85.56 | 88.89 | 100 | 98.89 | 93.33 | t
2 | 211 | 25.5 | 58.89 | 58.89 | 100 | 100 | 79.44 | t
3 | 23.5 | 24 | 96.67 | 78.89 | 100 | 98.89 | 93.67 | t
4 | 214.5 | 20.5 | 100 | 85.56 | 83.33 | 98.89 | 91.94 | t
5 | 22 | 27.5 | 100 | 96.67 | 100 | 100 | 99.17 | t
6 | 22 | 27.5 | 97.7 | 96.67 | 100 | 91.11 | 96.39 | t
7 | 211 | 23.5 | 98.89 | 90 | 100 | 88.89 | 94.44 | t
8 | 210 | 2ā1.5 | 61.11 | 51.11 | 53.33 | 87.78 | 63.33 |
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