Parameter optimization of a motorized spindle lubrication system using biogeography-based optimization

Abstract

Using response surface methodology, two-target parameter mathematical models for a 100MD60Y4 motorized spindle are established using biogeography-based optimization. Air supply pressure, fuel supply rate, and oil supply interval are the independent variables, while the spindle temperature increase and oil mist PM2.5 cumulative volume distribution percentage are the response variables. Biogeography-based optimization is used to find a set of optimal lubrication system parameters with the constraint of a small temperature increase in the motorized spindle at 30,000 r/min while considering the influence of oil mist particle size on environmental quality. After lubrication system parameter optimization, comparing the particle size distribution density and temperature increase between the biogeography-based optimization model’s calculated values and the experimental test results, the errors were 1.8% and 1.17%, respectively.