Rolling Element Bearing Performance Degradation Assessment Using Variational Mode Decomposition and Gath-Geva Clustering Time Series Segmentation

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/ijrm/volume-2017/2598169/figures/2598169.fig.0014a.svgz" name="2598169.fig.0014a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>BLIMF1’s envelope</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/ijrm/volume-2017/2598169/figures/2598169.fig.0014b.svgz" name="2598169.fig.0014b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>BLIMF2’s envelope</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/ijrm/volume-2017/2598169/figures/2598169.fig.0014c.svgz" name="2598169.fig.0014c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>BLIMF3’s envelope</td></tr></table>

<div>The envelope spectrum of BLIMF1 to BLIMF3 of #2600.</div>

International Journal of Rotating Machinery

fig14

Figure 14

Figure 14: Rolling Element Bearing Performance Degradation Assessment Using Variational Mode Decomposition and Gath-Geva Clustering Time Series Segmentation 

Figure 14 | Rolling Element Bearing Performance Degradation Assessment Using Variational Mode Decomposition and Gath-Geva Clustering Time Series Segmentation 