Research Article
A Fault Diagnosis Model for Rotating Machinery Using VWC and MSFLA-SVM Based on Vibration Signal Analysis
Table 2
Comparison results of training classification.
| | Type | BPNN positive/total accuracy | ACROA-SVM positive/total accuracy | SFLA-SVM positive/total accuracy | MSFLA-SVM positive/total accuracy | Average accuracy (%) |
| | Normal | 42/45
93.333% | 45/45
100.000% | 45/45
100.000% | 45/45
100.000% | 98.333 | | EAF | 41/45
91.111% | 44/45
97.778% | 43/45
95.556% | 45/45
100.000% | 96.111 | | BPF | 40/45
88.889% | 42/45
93.333% | 42/45
93.333% | 43/45
95.556% | 92.778 | | SRWF | 42/45
93.333% | 44/45
97.778% | 44/45
97.778% | 44/45
97.778% | 96.667 | | Average accuracy (%) | 91.667 | 97.222 | 96.667 | 98.334 | |
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