| AerMet100 ultra-high strength steel has high hardness,high strength,high toughness,corrosion resistance,high temperature resistance and other advantages,widely used in the aerospace field.As a typical difficult-to-machine material,AerMet100 ultra-high-strength steel cutting process has serious problems such as tool wear,short tool life and poor machining quality,which seriously restrict the improvement of cutting efficiency.This thesis takes AerMet100 ultra-high strength steel as the research object,and investigates in depth the application effect and mechanism of action of Cryogenic Minimum Quantity Lubrication(CMQL)milling of AerMet100ultra-high strength steel.The experimental results of the conventional cast machining method and the low-temperature air-cooled trace lubrication machining method are compared and the main research work is as follows:Based on the classical cutting theory,right angle and oblique angle cutting force models are established.Considering the effect of temperature,a tool wear model is established and a detailed study is made on the friction mechanism of the metal cutting process,the cooling and lubrication mechanism of the cutting medium,and the chip formation and chip breaking mechanism.Milling simulation using AdvantEdge software to compare cutting temperature,stress-strain and cutting force under two machining conditions to analyse the simulation optimisation of CMQL cutting AerMet100 ultra-high strength steel.Tool wear cutting experiments with different cutting parameters were designed to compare the macroscopic wear process,microscopic wear morphology and tool wear mechanism of the two machining methods.The results show that CMQL machining has less residue on the tool surface,lower wear values and no failure,and better inhibition of oxidative wear at large cutting rates.Single-factor experiments on tool life were designed to investigate the effect of depth of cut,feed and cooling temperature on the pattern of tool life.The comparison of the experimental results revealed that the tool life was improved by 121%.An empirical prediction model of tool life under CMQL conditions was established for the orthogonal experiments and the accuracy of the model was verified by statistical analysis.Based on a single factor test,the orthogonal test method was used to explore the effect of CMQL on the surface quality of workpieces.The surface roughness index prediction model was established by combining height characteristic parameters(Ra,Rp,Rv)and spacing characteristic parameters(Rsk,Rku)with the dominance rate as the index.The results show that CMQL machined workpieces have lower Ra values,smooth surface contours and reduced pitted wear,with an average dominance rate of16% and a significant optimisation effect.Surface roughness response surface experiments were carried out under CMQL conditions,and the linear,2FI,quadratic and cubic term models were validated by sequential variation analysis and misfit term analysis.The regression analysis,response surface and contour plots were used to study the effect law of the interaction between cooling temperature and cutting parameters on the surface roughness,and the optimized machining parameters were further obtained with an experimental average error rate of4.65% and an average optimization rate of 17.1%.The multi-objective optimization of tool life and surface roughness by applying genetic algorithm,the optimized tool life is improved by 19.67% and the surface roughness is optimized by 18.16%,which verifies the reliability of genetic algorithm.This study can provide theoretical support and application guidance for the application of CMQL in the milling of AerMet100 ultra-high strength steel and the optimisation of milling parameters. |
PDF Full Text Request