Application of Rotating Machinery Fault Diagnosis Based on Deep Learning

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">References</td><td class="align_center">Optimizing method</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">[<a href="/journals/sv/2021/3083190/#B71" target="_blank">71</a>, <a href="/journals/sv/2021/3083190/#B72" target="_blank">72</a>]</td><td class="align_center">Batch normalization (BN)</td></tr><tr><td class="align_left">[<a href="/journals/sv/2021/3083190/#B73" target="_blank">73</a>]</td><td class="align_center">Differential evolution/resilient backpropagation approach</td></tr><tr><td class="align_left">[<a href="/journals/sv/2021/3083190/#B74" target="_blank">74</a>]</td><td class="align_center">Particle swarm optimization (PSO)</td></tr><tr><td class="align_left">[<a href="/journals/sv/2021/3083190/#B75" target="_blank">75</a>]</td><td class="align_center">Harmony search (HS)</td></tr><tr><td class="align_left">[<a href="/journals/sv/2021/3083190/#B76" target="_blank">76</a>]</td><td class="align_center">Chaotic firefly algorithm (CFA)</td></tr><tr><td class="align_left">[<a href="/journals/sv/2021/3083190/#B76" target="_blank">76</a>, <a href="/journals/sv/2021/3083190/#B77" target="_blank">77</a>]</td><td class="align_center">Hybrid diagnostic model</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Summary of fault diagnosis based on optimization algorithm and AE model.</div>

Shock and Vibration

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Table 3

Table 3: Application of Rotating Machinery Fault Diagnosis Based on Deep Learning 