Research on Feature Fusion Method of Mine Microseismic Signal Based on Unsupervised Learning

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="7"><hr/></td></tr><tr class="thead"><td class="align_left">Decomposition layer</td><td class="align_center">3</td><td class="align_center">4</td><td class="align_center">5</td><td class="align_center">6</td><td class="align_center">7</td><td class="align_center">8</td></tr><tr><td class="thead-hr" colspan="7"><hr/></td></tr><tr><td class="align_left"><i>r</i><sub><i>k</i></sub></td><td class="align_center">0.9127</td><td class="align_center">0.7958</td><td class="align_center">0.6620</td><td class="align_center">0.4620</td><td class="align_center">0.4578</td><td class="align_center">0.4563</td></tr><tr class="table-tr"><td colspan="7"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Correlation coefficient of energy proportion of each decomposition layer wavelet packet.</div>

Shock and Vibration

tab3

Table 3

Table 3: Research on Feature Fusion Method of Mine Microseismic Signal Based on Unsupervised Learning 