【作者】 陈涛；

【导师】 刘献礼；

【作者基本信息】 哈尔滨理工大学 ， 机械制造及其自动化， 2009， 博士

【摘要】 硬态切削技术是近20年来迅速发展起来的先进制造技术,由于其具有加工效率高、加工柔性好、能耗低、污染小等优势,因而在淬硬钢精密加工领域具有广阔的应用前景。然而,对于这一新技术,在其理论研究尤其是硬态切削过程的建模与表面完整性预测方面缺少系统、全面地研究,使得有效预测和控制硬态切削加工表面完整性的理论基础尤显不足,严重阻碍了其在实际生产中的推广和应用。本文以PCBN刀具精密车削淬硬钢GCr15为研究对象,通过理论分析结合实验研究和数值模拟等方法,进行了精密硬车过程中绝热剪切行为模拟、切削力预测、表面完整性实验及表面完整性预测等方面的研究,为硬态切削加工技术推广应用提供理论依据和技术支撑。通过有限元模拟和实验相结合的方法,研究了绝热剪切行为作用下的切削力动态特征、绝热剪切带切削热的分布特征、锯齿形切屑形成过程和切屑的变形特征,以及刀具刃口几何参数和切削参数对切削力、切削温度,切屑形态和工件表层残余应力的影响规律。建立了基于刀-屑界面摩擦行为的精密硬车过程切削力模型,其中包括刀-屑摩擦界面切削力和切削负载的经验关系、圆弧切削刃等效变换、直角切削与三维切削变换和切削力系数求解等方面的研究。该模型实现了直角切削向斜角切削、斜角切削向三维切削的变换,使得直角切削模型中各种参数的计算结果可以移植到复杂三维切削计算过程中。在系统的切削实验和理论分析基础上,研究了切削用量和刀具几何参数以及各影响因素间相互作用对硬态切削加工表面粗糙度的影响;研究了高速切削条件下,切削力和切削热综合作用下的刀具磨损对表面粗糙度、残余应力的分布特征和白层的产生及其特征的影响规律。结果表明,随着刀具磨损和切削速度的增大,加工表面易产生残余拉应力,但残余压应力层深却随之增大;当切削速度达到200m/min时,即使PCBN刀具后刀面在无磨损状态下,加工表面也存在着白层,且当切削速度提高或刀具后刀面磨损量继续增大时,白层厚度明显增大,呈不均匀状熔附于工件表面上。运用反应曲面法建立了多参数条件下硬态切削表面粗糙度预测模型;运用BP人工神经网络方法,以刀具几何参数和切削参数为输入量,以残余应力和白层的特征值为输出量,建立表层残余应力和表面白层预测模型;最后,用Matlab软件开发了PCBN刀具精密硬车表层残余应力、表面白层和表面粗糙度的预测系统,实现了对精密硬车表面完整性较高精度的预测。更多还原

【Abstract】 Hard turning is one of the advanced manufacturing technologies in the last two decades. It is applied to precision process of hardened steel because of its high machining efficiency, good machining flexibility, low energy consumption and pollution. However, as for the new technology, there is a lack of systematic and thorough study in its theory, especially in the modeling and prediction of hard turning, which makes the theoretical basis insufficient that can predict and control effectively surface integrality of machined workpiece in hard turning, and prevents its popularization and application to practical production.In this work, the simulation of adiabatic shear behavior, prediction of cutting force, experiment and prediction of surface integrality are studied by means of combining theoretical analysis, experimental study and numerical simulation in high speed precision cutting of hardened steel GCr15 with PCBN tools, which provides an important theoretical basis and technological support for the further development, popularization and application of hard turning process.By using the method of FEM simulation and experiment, under the effect of adiabatic shear behavior, dynamic characteristics of cutting force, distribution characteristics of cutting temperature in adiabatic shear band, formation and deformation characteristics of serrate chip are investigated. The effect of tool edge and cutting parameters on cutting force, cutting temperature, chip morphology and residual stress on workpiece surface is also studied.Based on friction behavior on tool-chip interface, the cutting force model of precision hard turning is built, which involves the research into experimental relationship of cutting force and cutting load on tool-chip friction interface, equivalent transformation of radius cutting edge, transformation between orthogonal cutting and 3D cutting, calculation of cutting force coefficient. The model realizes the transformation from orthogonal cutting to oblique cutting, then to 3D cutting, which can make calculation results of all parameters in orthogonal cutting model transplanted into complex 3D cutting.Based on systematic cutting experiment and theoretical analysis, the effect of cutting parameters, tool parameters and factor interaction on surface roughness of machined workpiece in hard turning is studied. In addition, the effect of tool wear which is under the joint influence of cutting force and temperature in high-speed cutting, on surface roughness, distribution characteristics of residual stress, formation and characteristics of white layer is also investigated. The results are that with the increase of the tool wear and cutting speed, the surface of the machined workpiece tends to generate tensile residual stresses whose depth increases; when cutting speed reaches to 200m/min, there exists white layer on the surface of machined workpiece even though the flank of PCBN tool is in a fresh state, and with the further increase of cutting speed or flank wear of cutting tool, white layer becomes clearly thicker and uneven on the workpiece surface.The prediction model of surface roughness in hard turning of different parameters is built by RSM, and the prediction models of residual stress and white layer on surface are built using BP artificial neural network, which defines tool parameters and cutting parameters as input value, and the values of residual stress and white layer characteristics as output. Finally, MATLAB is used to develop prediction system of the residual stress, surface white layer, and surface roughness in precision hard turning with PCBN tools. The system has realized higher-accuracy prediction of surface integrality in precision hard turning.更多还原