【作者】 张宇；

【导师】 卢晓红； 褚金奎；

【作者基本信息】 大连理工大学 ， 机械工程（专业学位）， 2025， 硕士

【摘要】 镍基高温合金Inconel 718具有优良的高温强度、热稳定性和抗热疲劳性能,可以很好地满足航空航天、生物医学等领域对高温环境下具有较高强度和耐腐性的微小零部件的需求。但由于Inconel 718具有强度高、导热率低及硬质点多等特点,是典型难加工材料。激光辅助微铣削通过激光辅助加热软化切削区,能有效降低切削力,是实现Inconel718微小零部件高质、高效加工的潜在技术手段。然而,在激光辅助微铣削过程中,切削力降低对微铣刀磨损起抑制作用,激光辅助加热导致切削区温度急剧升高对微铣刀磨损有促进作用,在这种复杂的力热耦合作用下,微铣刀磨损规律复杂,难以有效预测;如何兼顾刀具磨损和加工效率进行工艺参数选择也是难题。针对上述难题,本文开展了Inconel 718激光辅助微铣削刀具磨损预测及工艺参数优化研究,具体研究内容如下:（1）激光辐照区域温度场分析与激光辅助微铣削Inconel 718过程仿真。分析激光辐照Inconel 718工件的热传递过程,根据能量守恒定律,并结合高斯移动热源模型,对激光加热Inconel 718工件预热温度场进行数值计算,为激光辅助微铣削的激光参数选择提供依据,并作为刀具磨损有限元仿真中工件的初始温度。确定了刀具及工件材料参数,建立了微铣刀和工件模型,实现了基于DEFORM-3D激光辅助微铣削Inconel 718过程仿真模型,并通过实验验证了仿真模型的有效性。（2）激光辅助微铣削Inconel 718微铣刀磨损预测模型。通过设置Usui磨损本构模型,实现了微铣刀磨损深度的预测。将仿真得到的刀具磨损深度与切削时间通过计算得出磨损率,并通过几何转化变为刀具相对直径减少率。开展了激光辅助微铣削Inconel718实验,使用3D表面光学轮廓仪进行切削后刀具直径测量并计算出相对直径减少率,验证了模型的有效性。实现了激光辅助微铣削Inconel 718的刀具磨损量预测。（3）镍基高温合金Inconel 718激光辅助微铣削工艺参数优化。选取主轴转速n、每齿进给量f_z、轴向切深a_p和激光功率P为影响因素,进行了四因素四水平L₁₆（4⁴）正交试验,并进行了极差分析。建立了刀具磨损率多项式回归预测模型,并对模型的预测精度和统计意义进行了评估。最后以材料去去除率最大和刀具磨损率最小为优化目标,基于遗传算法实现了激光辅助微铣削Inconel 718工艺参数优化,获得了Pareto最优解集。本文研究成果为实现激光辅助微铣削刀具磨损预测、解决镍基高温合金微小零件加工中存在的刀具寿命低和加工效率低的问题探索了可行之路,对解决其他难加工材料激光辅助微铣削加工难题也具有借鉴意义。更多还原

【Abstract】 Nickel-based superalloy Inconel 718 has excellent high temperature strength,thermal stability and thermal fatigue resistance,which can well meet the needs of aerospace,biomedical and other fields for small parts with high strength and corrosion resistance in high temperature environment.However,Inconel 718 is a typical difficult-to-machine material due to its high strength,low thermal conductivity and hard particles.Laser-assisted micro-milling softens the cutting zone by laser-assisted heating,which can effectively reduce the cutting force.It is a potential technical means to achieve high-quality and efficient processing of Inconel 718 micro-parts.However,in the process of laser-assisted micro-milling,the decrease of cutting force inhibits the wear of micro-milling tool,and the sharp increase of cutting zone temperature caused by laser-assisted heating promotes the wear of micro-milling tool.Under this complex thermo-mechanical coupling,the wear law of micro-milling tool is complex and difficult to predict effectively.How to balance tool wear and machining efficiency for process parameter selection is also a difficult problem.In view of the above problems,this paper carried out research on tool wear prediction and process parameter optimization of Inconel 718 laser-assisted micro-milling.The specific research contents are as follows:（1）Temperature field analysis of laser irradiation area and simulation of laser-assisted micro-milling Inconel 718 process.The heat transfer process of Inconel 718 workpiece irradiated by laser is analyzed.According to the law of conservation of energy and the Gaussian moving heat source model,the preheating temperature field of Inconel 718 workpiece heated by laser is numerically calculated,which provides a basis for the selection of laser parameters for laser-assisted micro-milling and serves as the initial temperature of the workpiece in the finite element simulation of tool wear.The material parameters of the tool and the workpiece are determined,and the model of the micro-milling tool and the workpiece is established.The simulation model of the laser-assisted micro-milling Inconel 718 process based on DEFORM-3D is realized,and the validity of the simulation model is verified by experiments.（2）The wear prediction model of laser-assisted micro-milling Inconel 718 micro-milling tool.By setting the Usui wear constitutive model,the prediction of the wear depth of the micro-milling tool is realized.The wear rate is calculated by calculating the tool wear depth and cutting time obtained by simulation,and the relative diameter reduction rate of the tool is transformed by geometry.The laser-assisted micro-milling experiments of Inconel 718 are carried out.The3D surface optical profiler is used to measure the tool diameter after cutting,and the validity of the model is verified.The tool wear prediction of laser-assisted micro-milling of nickel-based superalloy Inconel 718 is realized.（3）Optimization of laser-assisted micro-milling process parameters of nickel-based superalloy Inconel 718.The spindle speed n,feed per tooth f_z,axial cutting depth a_p and laser power P are selected as the influencing factors,and the four-factor four-level L₁₆（4⁴）orthogonal test is carried out,and the range analysis is carried out.The polynomial regression prediction model of tool wear rate is established,and the prediction accuracy and statistical significance of the model are evaluated.Finally,taking the maximum material removal rate and the minimum tool wear rate as the optimization objectives,the process parameters of laser-assisted micro-milling Inconel 718 are optimized based on genetic algorithm,and the Pareto optimal solution set is obtained.The research results of this paper explore a feasible way to realize the prediction of tool wear in laser-assisted micro-milling and solve the problems of low tool life and low machining efficiency in the processing of nickel-based superalloy micro-parts.It also has reference significance for solving the problems of laser-assisted micro-milling of other difficult-to-machine materials.更多还原