Photovoltaic Module Fault Detection Based on Deep Learning Using Cloud Computing

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">ID 1</td><td class="align_center">ID 2</td><td class="align_center">ID 3</td><td class="align_center">ID 4</td><td class="align_center">ID 5</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Burn marks</td><td class="align_center">Delamination</td><td class="align_center">Discoloration</td><td class="align_center">Glass breakage</td><td class="align_center">Snail trail</td></tr><tr><td class="align_left">100%</td><td class="align_center">96.66%</td><td class="align_center">100%</td><td class="align_center">100%</td><td class="align_center">96.66%</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Results of performance comparison of different faults in a PVM with no defect condition.</div>

Scientific Programming

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Table 4

Table 4: Photovoltaic Module Fault Detection Based on Deep Learning Using Cloud Computing 