A New Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Fault Diagnosis

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Feature</td><td class="align_center">Time-domain statistics</td><td class="align_center">Frequency-domain statistics</td><td class="align_center">The proposed feature</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Accuracy (%)</td><td class="align_center">59.55</td><td class="align_center">70.33</td><td class="align_center">93.09</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>RBF recognition results based on different features.</div>

Shock and Vibration

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Table 5

Table 5: A New Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Fault Diagnosis 