A Diagnosis Framework for High-reliability Equipment with Small Sample Based on Transfer Learning

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left"><i>Pump flow (L/h)</i></td><td class="align_center"><i>Output pressure (Kpa)</i></td><td class="align_center"><i>Voltage (V)</i></td><td class="align_center"><i>Current (A)</i></td><td class="align_center"><i>Oil leakage (ml/min</i></td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">12000</td><td class="align_center">≥73</td><td class="align_center">115</td><td class="align_center">≤5.5</td><td class="align_center">0</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Main working parameters of the airborne fuel pump.</div>

Complexity

tab1

Table 1

Table 1: A Diagnosis Framework for High-reliability Equipment with Small Sample Based on Transfer Learning 