Orthogonal experimental design and parameter optimization of an oil multi-gradient filtration device based on an applied electric field

Abstract

Particulate pollutants in lubricating oils tend to increase the friction and wear of machine components, resulting in machine failure. This study proposes an oil multi-gradient filtration device employing an applied electric field for the effective removal of solid particles. Combined with the orthogonal test design, the effects of various control parameter combinations on the oil–solid separation were studied, aiming to achieve a lower pressure drop and higher filtration device efficiency. The degree of significance of the influence of each factor on the pressure drop of the filtration device and filtration efficiency was determined through a significance analysis. A regression model of the influence of the pressure drop and filtration efficiency under multi-factor conditions was established to define the relationship between the pressure drop, filtration efficiency, and control parameters. A dual-objective optimisation based on a non-dominated sorting genetic algorithm (NSGA-II) was then performed. The optimum parameters for achieving a low-pressure-drop and high-efficiency filtration device were determined. The significance of the influence of the parameters on the pressure drop of the filter device followed the order: inlet flow rate > oil viscosity > electric field strength, indicating that the pressure drop was predominantly controlled by the inlet flow rate. The significance on the influence of the parameters on the filtration efficiency followed the order: electric field strength > oil viscosity > inlet flow rate, indicating that the filtration efficiency is primarily controlled by the electric field strength. Based on the NSGA-II, the optimal parameters are E = 2 kV/mm, flow rate = 0.2 m/s, and viscosity = 12 mPa·s. Using these optimal parameters, the pressure drop was minimized and did not exceed 48,325 Pa, and the filtration efficiency reached 99.96 %.