Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/mpe/volume-2016/7906834/figures/7906834.fig.003a.svgz" name="7906834.fig.003a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Undamaged with air jets not turned on</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/mpe/volume-2016/7906834/figures/7906834.fig.003b.svgz" name="7906834.fig.003b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Undamaged with air jets on</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/mpe/volume-2016/7906834/figures/7906834.fig.003c.svgz" name="7906834.fig.003c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Damaged with air jets on</td></tr></table>

<div>Exemplary of time-frequency representation estimated for wind turbine vibration (left) and acoustic (right) signals with different conditions.</div>

Mathematical Problems in Engineering

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Figure 3

Figure 3: Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis 