PCD刀具车削钛合金Ti-6AI-4V的研究

本文通过正交试验研究了PCD刀具车削钛合金Ti-6A14V时,动态切削力和表面粗糙度随切削用量的变化规律,并分别以Ra、Rz为指标进行了方差分析.试验结果表明:x向和Y向动态切削力随切削用量的变化很小,而z向相对较大.动态切削力随进给量和切削深度的增加而增加,其中在切削深度为0.1 mm的情况下,切削力出现了较大的波动.进给量和切削深度均对Ra、Rz有显著影响,其中进给量对Ra影响较大,切削深度对Rz影响较大.     

PCD刀具车削钛合金Ti-6Al-4V的研究

本文通过正交试验研究了PCD刀具车削钛合金Ti-6A l-4V时,动态切削力和表面粗糙度随切削用量的变化规律,并分别以Ra、Rz为指标进行了方差分析。试验结果表明:x向和y向动态切削力随切削用量的变化很小,而z向相对较大。动态切削力随进给量和切削深度的增加而增加,其中在切削深度为0.1 mm的情况下,切削力出现了较大的波动。进给量和切削深度均对Ra、Rz有显著影响,其中进给量对Ra影响较大,切削深度对Rz影响较大。     

高速干铣削高强钢铣削力及表面粗糙度研究

选用PVD—TiAlN-TiN硬质合金涂层刀具,进行高速干铣削AISI4340高强钢正交试验,研究铣削力及加工表面粗糙度随切削参数的变化,并建立铣削力及加工表面粗糙度与切削参数之间的经验模型。分析结果表明:每齿进给量和铣削速度对主切削力Fz影响较大,径向切削深度对加工表面粗糙度Ra影响较小。建立的铣削力及加工表面粗糙度经验模型,经过检验,相对误差较小。涂层刀具高速铣削AISI4340钢时,采用较小的轴向切削深度和每齿进给量以及较大的铣削速度和径向切削深度有利于得到较小的铣削力和加工表面粗糙度。     

精车参数对连杆衬套表面粗糙度影响

数控车床精车后的连杆衬套表面粗糙度是影响其使用性能的关键因素之一。以某型号柴油机的连杆衬套为对象,采用单因素试验法,以切削速度、进给量以及切削深度为试验变量,以精车后表面粗糙度(Ra和Rz值)为评价指标,进行车削试验,研究各精车参数对连杆衬套表面粗糙度的影响。结果表明,精车后连杆衬套的粗糙度随切削速度增大而增大,随进给量增大先减小后增大,随切削深度的增大而增大。其中,进给量对精车件表面粗糙度(Ra和Rz)的影响最大。     

CVD金刚石厚膜刀具切削参数对切削力及粗糙度影响的研究

为了探究CVD金刚石厚膜刀具切削参数(包括刀具后角、刀尖圆弧半径、切削速度、进给量和切削深度)对切削力和被加工表面粗糙度影响的初步规律,采用单因素方法进行了一系列CVD金刚石厚膜刀具车削仿真和试验研究。结果表明:AdvantEdge有限元仿真软件模拟切削力过程有一定的准确性;在试验参数范围内,随着刀具后角的增大,切削力和表面粗糙度都是先减小后增大,当后角为11°时,切削力和表面粗糙度值最小;随着刀尖圆弧半径的增大,切削力逐渐增大,而表面粗糙度则逐渐减小;随着切削速度的增大,切削力和表面粗糙度都是先增大后减小,当切削速度为90m/min时,切削力和表面粗糙度值最大;随着进给量的增大,切削力和表面粗糙度都显著增大;随着切削深度的增大,切削力和表面粗糙度都逐渐增大,但切削深度对表面粗糙度的影响较小。     

微细铣削不锈钢310S表面完整性试验研究

目的揭示微细铣削下的切削深度ap、进给量f、切削速度v对不锈钢310S表面完整性的影响规律,为优化不锈钢310S的切削工艺提供参考。方法基于响应曲面方法,采用涂层硬质合金微直径铣刀,对不锈钢310S进行了铣削加工试验,对表面粗糙度、表面形貌和显微硬度的数据和信息进行采集并分析,进行多元非线性回归,建立了表面粗糙度Ra与切削参数之间的映射关系,对多元回归方程进行了显著性检验。结果得到切削参数ap、v、f显著度分别为0.099、0.620、0.011。基于曲面响应法的试验数据及数学模型,直观地绘制了ap、v、f对表面粗糙度Ra、表面形貌和显微硬度的影响规律图。结论在一定的切削加工参数范围内,进给量f对微细铣削不锈钢310S表面粗糙度Ra的影响最显著,其次是切削深度ap,切削速度v的影响最小。表面留有摆线状加工痕迹,顺铣侧的残留物分布多于逆铣侧。切削深度ap对310S试件表层显微硬度的影响最显著,其次是切削速度v。减小进给量f是降低不锈钢310S表面粗糙度的有效加工方法。     

基于动态力学模型分析的钛合金切削过程进给量对表面质量的影响规律

目的建立单自由度工件-刀具振动系统动力学模型,定量研究进给量对钛合金Ti-6Al-4V切削力和振动加速度的影响规律。方法采用改变进给量的单因素试验,选用涂层硬质合金刀具车削钛合金Ti-6Al-4V,通过DYTRAN加速度传感器、YDCB-Ⅲ05三向压电测力系统对试验过程中切削振动和切削力进行检测,运用MATLAB、Origin软件对采集的振动加速度和切削力信号进行处理和分析,采用120mm位相光栅干涉粗糙度轮廓仪(Talysurf PGI840)测量其表面粗糙度。结果当进给量分别为0.1、0.15、0.2、0.24、0.3 mm/r时,振动加速度的均方根分别为0.2413g、0.3299g、0.3945g、0.4468g、0.5737g;算数平均高度Ra分别为0.5383、0.9391、1.4781、1.9849、3.0117μm;平均谷深度Rz分别为3.1846、4.6445、6.3059、8.3383、11.6506μm,随进给量的增大,切削力、振动加速度和表面粗糙度均增大。结论当刀具进给量增大时,刀具与工件之间的接触面积增大,摩擦力增大,从而引起切削力稳态分量的增大,根据单自由度工件-刀具振动系统动力学模型可知,切削力稳态分量增大,切削振动加速度随之增大,会使刀尖位移增大,造成表面粗糙度值随着进给量的增大而增大。     

漂珠/镁合金可溶复合材料切削加工表面粗糙度及其预测模型

为研究漂珠/镁合金可溶复合材料的切削加工质量,采用正交试验法对漂珠/镁合金可溶复合材料进行了不同切削参数下的切削加工试验。研究结果表明:进给量对切削加工表面粗糙度影响最大,其次是切削深度,切削速度影响最小;试样表面微观形貌呈平行沟槽状,且其深度和宽度随粗糙度的增大而增大;进给量通过影响试样表面相邻锯齿峰之间的宽度影响试样表面粗糙度;运用回归分析法建立了漂珠/镁合金可溶复合材料切削加工表面粗糙度预测模型,并通过方差分析和实验验证表明模型拟合良好,可以实现对复合材料切削加工表面粗糙度的预测和控制。     

车削钛合金TC4的表面粗糙度预测模型构建

采用中心复合试验对钛合金进行了车削试验,分析了切削三要素切削速度、进给量、切削深度对表面粗糙度的影响。基于二阶响应面法建立了表面粗糙度的预测模型,对回归方程进行了显著性检验,并对切削参数影响表面粗糙度的显著性进行了比较。结果表明:在试验采用的切削参数范围内,进给量对切削表面粗糙度的影响最大,切削深度次之,切削速度影响最小;预测模型回归显著,置信度高,可指导加工前合理切削参数的选择,以达到对表面粗糙度进行预测和控制的目的。     

钛合金螺旋铣孔切削工艺的正交优化与试验分析

目的稳健设计螺旋铣孔对难加工材料钛合金加工件的切削参数(切削深度、每齿进给量和主轴旋转速度)。方法用正交优化法制定一套试验方案并实施,使用粗糙度量仪、三坐标、显微镜等对钛合金孔表面粗糙度(Ra)、孔径精度和出口端毛刺高度进行测量和分析;在此基础上,利用试验数据分析影响因素水平极差和贡献率,优选出一组切削参数组合(主轴旋转速度2000 r/min、每齿进给量为0.07 mm和切削深度0.25 mm/r),以此为基准,对待加工钛合金工件表面粗糙度进行预测;为进一步验证预测值满足孔表面质量标准,然后对钛合金加工件试验分析。结果结果表明,孔表面粗糙度介于0.55~0.75μm,孔径精度介于H7~H9,很好地达到了航天或汽车工业对钻孔粗糙度的技术要求。结论由此可见,使用该方法,不仅可获得稳健设计切削参数,还可改善钛合金螺旋铣孔切削工艺。     

Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA

The present paper outlines an experimental study to investigate the effects of cutting parameters on finish and power consumption by employing Taguchi techniques. The high speed machining of AISI 1045 using coated carbide tools was investigated. A combined technique using orthogonal array and analysis of variance was employed to investigate the contribution and effects of cutting speed, feed rate and depth of cut on three surface roughness parameters and power consumption. The results showed a significant effect of cutting speed on the surface roughness and power consumption, while the other parameters did not substantially affect the responses. Thereafter, optimal cutting parameters were obtained.     

PCD刀具微细车削硬铝合金的表面质量研究

在微细车削硬铝合金正交试验中,分析了切削参数(包括切削速度、进给量、切削深度)对表面粗糙度和表面显微硬度的影响规律,建立了表面粗糙度预测模型,并进行了回归方程和回归系数的显著性检验。结果表明:进给量对微细车削表面粗糙度的影响最大,切削速度次之,切削深度影响最小,较大的切削速度不仅使机床振动加剧从而使表面粗糙度值增加,而且切削中热量不易散发,表面产生加工硬化。考虑机床动态特性选择合适的切削速度避开机床振动,以及采用较小的进给量、合理的切削深度可获得最好的微细车削表面质量。     

Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool

The present work concerns an experimental study of hard turning with CBN tool of AISI 52100 bearing steel, hardened at 64 HRC. The main objectives are firstly focused on delimiting the hard turning domain and investigating tool wear and forces behaviour evolution versus variations of workpiece hardness and cutting speed. Secondly, the relationship between cutting parameters (cutting speed, feed rate and depth of cut) and machining output variables (surface roughness, cutting forces) through the response surface methodology (RSM) are analysed and modeled. The combined effects of the cutting parameters on machining output variables are investigated while employing the analysis of variance (ANOVA). The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of machining parameters with respect to objectives (surface roughness and cutting force values). Results show how much surface roughness is mainly influenced by feed rate and cutting speed. Also, it is underlined that the thrust force is the highest of cutting force components, and it is highly sensitive to workpiece hardness, negative rake angle and tool wear evolution. Finally, the depth of cut exhibits maximum influence on cutting forces as compared to the feed rate and cutting speed.     

Cutting performance of diamond tools during ultra-precision turning of electroless-nickel plated die materials

This study is an attempt (a) to observe the wear characteristic of diamond tool with 200 km cutting distance and to study the effects of wear on the surface roughness and cutting forces and (b) to optimize various cutting parameters such as depth of cut, feed rate, spindle speed and phosphorus content. The experimental results showed that tool wear was not so significant although some defects on rake face were observed after cutting 15.6 km. Further cutting showed that the surface roughness increases with cutting distance, and that the cutting forces were larger than thrust force at the beginning of cutting, but after cutting 130 km, thrust force became larger and increased rapidly. It was also observed that forces increase with the increase of depth of cut, spindle speed and feed rate, and decrease with the increase of phosphorus content of the plating. Depth of cut has no significant effect on surface roughness, while it increases with increase of feed rate and decreases with the increase of percentage of phosphorus content in the workpieces. In case of spindle speed, surface roughness decreases with the increase of spindle speed up to a certain value and then starts to increase with the increase of spindle speed.     

PVD硬质合金刀具加工NimonicC-263合金表面粗糙度的建模和分析

研究了加工Nimonic C-263合金时,切削参数（切削速度、给进速度、切削深度等）对表面粗糙度的影响。采用正交方法设计实验。评估了切削参数对表面粗糙度的影响,获得最小粗糙度的最优切削条件。采用响应面方法建立了切削参数和表面粗糙度的二次多项式模型。实验结果表明：在所考察的切削参数中,给进速度对表面粗糙度的影响最为显著,其次是切削速度。模型预测结果与实际结果吻合较好,表明所建立的模型能够用来有效地预测加工Nimonic C-263合金时的表面粗糙度。最后,对预测结果用加成定律进行了验证。     

Predictive machinability models for a selected hard material in turning operations

In this paper, empirical models for tool life, surface roughness and cutting force are developed for turning operations. Process parameters (cutting speed, feed rate, depth of cut and tool nose radius) are used as inputs to the developed machinability models. Two important data mining techniques are used; they are response surface methodology and neural networks. Data of 28 experiments when turning austenitic AISI 302 have been used to generate, compare and evaluate the proposed models of tool life, cutting force and surface roughness for the considered material.     

GA Approach for Optimization of Surface Roughness Parameters in Machining of Al Alloy SiC Particle Composite

Experiments were carried out using carbide turning inserts on AA7075/10?wt.% SiC (particle size 10-20???m) composites to get actual input values to the optimization problem, so that the optimized results are realistic. By using experimental data, the regression model was developed. This model was used to formulate the fitness function of the genetic algorithm (GA). This investigation attempts to perform the application of GA for finding the optimal solution of the cutting conditions minimum value of surface roughness. The analysis of this investigation shows that the GA technique is capable of estimating the optimal cutting conditions that yield the minimum surface roughness value. With the highest speed, the lowest feed rate, the lowest depth of cut, and the highest nose radius of the cutting conditions' scale, the GA technique recommends 1.039???m as the best minimum predicted surface roughness value. This means that the GA technique has decreased the minimum surface roughness value of the experimental sample data, regression modeling and desirability analysis by about 3%, 1%, and 2.8%, respectively.     

58SiMn高强度钢车削表面完整性的试验研究

目的研究58Si Mn高强度钢表面完整性评价指标受切削参数影响的变化规律。方法分别设计单因素和正交试验,采用涂层硬质合金刀具对58Si Mn高强度钢进行车削加工试验,通过采集相关数据,分别讨论了切削深度、进给速度和切削速度变化对表面粗糙度、残余应力、显微硬度和表层微观组织变化等方面的影响。结果进给速度对表面粗糙度的影响最显著,切削速度次之,切削深度的变化对表面粗糙度无直接影响。已加工表面的残余应力随切削速度和进给量的增大而增大。显微硬度随切削深度的增大而减小,随进给量的增大而增大,层深上的显微硬度则呈现先减小后增大的趋势。表层微观组织受切削速度影响不大,未出现明显的相变和晶粒歪曲。结论降低进给速度是减小工件表面粗糙度最直接有效的方法,提高切削速度并不能使表面粗糙度明显减小。工件表面的轴向和切向残余应力均为拉应力,为提高零件使用性能,应采取相应的措施使之转化为压应力。     

基于航空铸造钛合金Ti-6Al-4V高速铣削参数的表面质量及切削效率优化

目的研究高速铣削参数对航空铸造钛合金Ti-6Al-4V表面质量的影响规律及交互作用,并基于高速铣削参数对表面质量和材料去除率进行优化。方法采用Box-Behnken设计和二次回归正交实验法,建立高速铣削参数与表面粗糙度的显著不失拟回归模型,获得铣削参数影响表面粗糙度的显著性差异,挖掘高速铣削参数交互作用与表面粗糙度的关系;基于表面粗糙度回归模型及材料去除率,采用遗传算法(GA),对高速铣削参数进行多目标优化。结果铣削参数影响航空铸造钛合金Ti-6Al-4V试件表面粗糙度的显著性顺序为:切削深度>每齿进给量>切削宽度>主轴转速,其中切削宽度和主轴转速、每齿进给量和主轴转速的交互作用较为明显。利用遗传算法对铣削参数优化后,Ti-6Al-4V表面粗糙度较优化前提高44%,材料去除率提高70%,遗传算法优化后的试件表面粗糙度显著降低,表面刀路行距减小,纹理平均高度降低。结论由实验验证可知,通过响应曲面建立表面粗糙度显著不失拟回归模型具有较高的预测精度,基于遗传算法优化获得的铣削参数可有效提高表面质量和切削效率,对保证航空铸造钛合金Ti-6Al-4V表面质量具有较好的指导意义。     

PCBN刀具高速铣削TC4钛合金切削性能与工艺参数优化研究

针对钛合金TC4(Ti-6Al-4V)的加工特性,采用PCBN刀具,基于单因素试验,研究高速铣削条件下工艺参数对切削力、切削振动等的影响规律,提出综合考虑切削力、切削振动、表面粗糙度的工艺参数优选方法。研究表明:切削力和切削振动随切削速度v和每齿进给量f_z的增大呈现一定的波动,随径向切深a_e和轴向切深a_p的增大而增大,切削振动受切削力影响较为显著。考虑切削性能,以材料切除率为优化目标,以切削力、切削振动和表面粗糙度等为约束条件,建立工艺参数优选模型,可得到不同约束条件下工艺参数的优选组合。