Research Article
A Fault Diagnosis Model for Rotating Machinery Using VWC and MSFLA-SVM Based on Vibration Signal Analysis
Table 3
Comparison results of testing classification.
| Type | BPNN positive/total classification | ACROA-SVM positive/total classification | SFLA-SVM positive/total classification | MSFLA-SVM positive/total classification | Average accuracy (%) |
| Normal | 13/15 86.667% | 15/15 100.000% | 15/15 100.000% | 15/15 100.000% | 96.667 | EAF | 13/15 86.667% | 13/15 86.667% | 14/15 93.333% | 14/15 93.333% | 90.000 | BPF | 12/15 80.000% | 13/15 86.667% | 13/15 86.667% | 13/15 86.667% | 85.000 | SRWF | 12/15 86.667% | 14/15 93.333% | 13/15 86.667% | 14/15 93.333% | 90.000 | Average accuracy (%) | 85.000 | 91.667 | 91.667 | 93.333 | ā |
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