Residual Stress Finite Element Analysis And Parameter Optimization Of Titanium Alloy In The High-speed Milling

Due to the superior physical properties such as high strength and high thermal intensity,the good low temperature performance, good corrosion resistance, etc., titanium alloy was widely used in many fields. Titanium alloy is a kind of hard processing material, however, it has a number of unfavorable the characteristics when cutting: high cutting temperature, high friction, serious tool wear, etc.. Using the advantages of high-speed cutting technology has been coming one of the effective means to solve this problem. Small cracks on the machine surface are mostly caused by stress change. Residual stress not only reduces the material strength, leading to the deformation or cracking occurred during processing, but also reduces the fatigue strength of materials after processing during natural cooling, resulting in quality problems. Optimizing the cutting parameters is one of the important methods to solve surface residual stress caused by the unreasonable cutting parameter selection.The paper established the finite element simulation model of high-speed milling titanium alloy, researched on the effect of the residual stress and optimized the cutting parameters.First of all, a finite element model of high-speed milling titanium alloy established; the paper used the ABAQUS finite element analysis software to establish the three dimensional finite element model of titanium alloy in high-speed milling, and simulate the high-speed milling process of titanium alloy Ti6Al4 V to analyze the effect of the cutting parameters on cutting force and cutting temperature.Surface residual stress was researched in the high-speed milling; On the premise of high-speed milling process simulation, the distribution of surface residual stress was analyzed,and the effect of cutting parameters on the residual stress was researched.Finally, the cutting parameter of high-speed wad optimized; A model of maximum surface residual stress regression was established. By using the hybrid genetic simulated annealing algorithm, cutting parameters on residual stress were optimized to gain the optimal cutting parameters combination, achieving high efficiency.