Study On Surface Characteristics And Process Optimization Of SCCO₂-MQL Ultrasonic Vibration Milling SiCp/Al Composites

With the wide application of SiCp/Al composite material in aerospace,automotive and other fields,the surface quality and mechanical properties of its production and processing requirements are increasingly high,but because of the difficult processing characteristics of SiCp/Al,also put forward no small challenge to its machining.Therefore,this paper adopts supercritical CO₂micro-lubrication（SCCO₂-MQL）compound ultrasonic vibration technology for milling SiCp/Al composites in combination with green and efficient production requirements,and studies the surface characteristics after machining,and optimizes the process parameters of this technology in combination with cutting and machining objectives.Firstly,the function and working principle of the supercritical CO₂micro-lubrication system are analyzed,and then the cooling effect of supercritical CO₂is investigated by analyzing the theory and physical properties of supercritical CO₂injection,and the force action analysis of SCCO₂-MQL droplets is conducted to investigate the conditions of factors affecting the jet droplets and the mechanism of penetration action;theoretical analysis of ultrasonic vibration-assisted milling is conducted to investigate its milling mechanism,and the action mechanism of ultrasonic-assisted milling is analyzed based on the kinetic model.Second,Comparative experiments were conducted under dry cutting,SCCO₂,SCCO₂-MQL,ultrasonic vibration and SCCO₂-MQL combined ultrasonic vibration conditions.The improvement of surface roughness and surface topography by process conditions（dry cutting,SCCO₂,SCCO₂-MQL,ultrasonic vibration and SCCO₂-MQL combined ultrasonic vibration）was investigated by comparative analysis of the test results.Based on SCCO₂-MQL ultrasonic vibration and single factor test under dry condition,the influences of milling parameters（milling speed,feed rate,milling depth）on the surface roughness and surface topography of SiCp/Al were studied.Then,the microhardness of the machined workpiece was detected,and the influence law of process environment and milling parameters on the machining hardening of the material was investigated;based on GRNN neural network,the machining hardening prediction model of SCCO₂-MQL ultrasonic vibration milling surface was constructed by combining the machining hardening test data.Finally,based on the response surface method,we designed an experiment with cutting speed,feed,cutting oil content and injection flow rate as experimental variables,and surface roughness and cutting force as evaluation indexes,and established a second-order response surface prediction model for surface roughness and cutting force by ANOVA to analyze the interactive effects of four parameter variables on two indexes;applied the MOPSO algorithm with crowding distance ranking to find the optimal solution for the SCCO₂-MQL milling SiCp/Al composites,and determined the best solution by Topsis for the optimal pareto solution set,and conducted experimental verification.