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The subsurface damage depth of grinding WC-10Co-4Cr coating with a cup wheel was investigated in an effort to address the issue that the subsurface damage will cause the coating's performance to deteriorate. The theoretical formula of single particle grinding force was obtained based on the principles of indentation fracture mechanics and grinding material removal theory. A theoretical subsurface damage depth prediction model was developed based on the cup wheel's surface grinding properties. The design of the single factor surface grinding test and the single point polishing test was to confirm the model's accuracy. Analysis was done on how various grinding parameters affected the workpiece's surface roughness and depth of subsurface damage. The maximum relative error is 15. 8%, and the predicted subsurface damage depth agrees with the measured value, according to the results. Surface roughness and subsurface damage depth rise with feed speed and grinding depth, but fall with spindle speed. The study has some theoretical significance for directing the process parameter optimization of cup wheel grinding of WC-10Co-4Cr coatings.

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JIANG Chen, E-mail:
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针对磨削WC-10Co-4Cr涂层产生的亚表面损伤会导致涂层性能下降的问题,开展杯形砂轮磨削WC-10Co-4Cr涂层的亚表面损伤深度研究。根据磨削材料去除理论和压痕断裂力学,得出单颗粒磨削力理论表达式;基于杯形砂轮平面磨削特点,建立亚表面损伤深度理论预测模型;设计单因素平面磨削试验及单点抛光试验以验证模型准确性;分析不同磨削参数对工件亚表面损伤深度与表面粗糙度的影响规律。研究表明,亚表面损伤深度预测值与实测值的变化趋势一致,最大相对误差为15.8%;亚表面损伤深度及表面粗糙度随磨削深度、进给速度的增加而增加,随主轴转速的增加而减少。研究对于指导杯形砂轮磨削WC-10Co-4Cr涂层加工参数优化具有一定价值。

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姜晨(通信作者),男,1978年生,安徽池州人,博士,教授,博士研究生导师;主要研究方向为精密加工及检测技术、制造过程智能化、微结构仿生表面设计与制造、CAM装备制造过程虚拟仿真技术;E-mail:
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沈先弟,男,1999年生,安徽安庆人,在读硕士研究生;主要研究方向为精密加工及检测技术;E-mail:

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沈先弟,男,1999年生,安徽安庆人,在读硕士研究生;主要研究方向为精密加工及检测技术;E-mail:

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沈先弟,男,1999年生,安徽安庆人,在读硕士研究生;主要研究方向为精密加工及检测技术;E-mail:

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Relevant parameters of WC-10Co-4Cr coating material

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参数Parameter值Value
弹性模量 Elasticity modulus E/GPa310
维氏硬度 Vickers hardness H/HV1 200
断裂韧性 Fracture toughness Kc/(MPa∙m)1/24.26
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WC-10Co-4Cr涂层材料的相关参数

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参数Parameter值Value
弹性模量 Elasticity modulus E/GPa310
维氏硬度 Vickers hardness H/HV1 200
断裂韧性 Fracture toughness Kc/(MPa∙m)1/24.26
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Test scheme of the planar grinding

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序号
No.
磨削深度
Grinding depth ap/μm
进给速度
Feed speed vw/(mm/s)
砂轮线速度
Linear speed of the grinding wheel vs/(m/s)
S1537.86
S210
S315
S41017.86
S52
S65
S71522.62
S85.24
S97.86
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平面磨削试验方案

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序号
No.
磨削深度
Grinding depth ap/μm
进给速度
Feed speed vw/(mm/s)
砂轮线速度
Linear speed of the grinding wheel vs/(m/s)
S1537.86
S210
S315
S41017.86
S52
S65
S71522.62
S85.24
S97.86
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Test scheme of the single-point polishing

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参数Parameter数值Value
转速Rotational speed/(r/min)400
抛光间隙Polishing gap/mm0.7
抛光时间Polishing time/min20
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单点抛光试验方案

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参数Parameter数值Value
转速Rotational speed/(r/min)400
抛光间隙Polishing gap/mm0.7
抛光时间Polishing time/min20
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Comparison between predicted and test values of the normal grinding force

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序号
No.
预测值
Predicted value Fns /N
试验值
Test value/N
绝对误差
Absolute error/N
相对误差
Relative error/%
S148.41747.60.8171.72
S291.25886.34.9585.75
S3132.328125.46.9285.53
S429.78527.32.4859.10
S560.19756.14.0977.30
S6155.420144.810.6157.33
S7274.846258.816.0466.20
S8132.328124.57.8286.29
S987.14781.75.4476.67
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法向磨削力预测值与试验值对比

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序号
No.
预测值
Predicted value Fns /N
试验值
Test value/N
绝对误差
Absolute error/N
相对误差
Relative error/%
S148.41747.60.8171.72
S291.25886.34.9585.75
S3132.328125.46.9285.53
S429.78527.32.4859.10
S560.19756.14.0977.30
S6155.420144.810.6157.33
S7274.846258.816.0466.20
S8132.328124.57.8286.29
S987.14781.75.4476.67
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Measurement results of workpiece surface roughness

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序号
No.
Ra1/μmRa2/μmRa3/μm平均值
Mean value Ra/μm
S04.1094.0664.5034.226
S10.0150.0160.0160.016
S20.0190.0220.0230.021
S30.0300.0320.0300.031
S40.0140.0150.0160.015
S50.0180.0170.0190.018
S60.0320.0300.0320.032
S70.0850.0810.0840.083
S80.0270.0300.0280.029
S90.0170.0160.0180.017
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工件表面粗糙度测量结果

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序号
No.
Ra1/μmRa2/μmRa3/μm平均值
Mean value Ra/μm
S04.1094.0664.5034.226
S10.0150.0160.0160.016
S20.0190.0220.0230.021
S30.0300.0320.0300.031
S40.0140.0150.0160.015
S50.0180.0170.0190.018
S60.0320.0300.0320.032
S70.0850.0810.0840.083
S80.0270.0300.0280.029
S90.0170.0160.0180.017
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杯形砂轮平面磨削WC-10Co-4Cr涂层亚表面损伤研究
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沈先弟 1 , 姜晨 1 , 姜臻禹 1 , 张逸轩 1 , 王玲奇 2 , 普桂元 2
机械强度 | ·疲劳·损伤·断裂·失效分析· 2025,47(7): 42-48
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机械强度 | ·疲劳·损伤·断裂·失效分析· 2025, 47(7): 42-48
杯形砂轮平面磨削WC-10Co-4Cr涂层亚表面损伤研究
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沈先弟1 , 姜晨1 , 姜臻禹1, 张逸轩1, 王玲奇2, 普桂元2
作者信息
  • 1.上海理工大学 机械工程学院,上海 200093
  • 2.上海市轴承技术研究所有限公司,上海 201800
  • 沈先弟,男,1999年生,安徽安庆人,在读硕士研究生;主要研究方向为精密加工及检测技术;E-mail:

通讯作者:

姜晨(通信作者),男,1978年生,安徽池州人,博士,教授,博士研究生导师;主要研究方向为精密加工及检测技术、制造过程智能化、微结构仿生表面设计与制造、CAM装备制造过程虚拟仿真技术;E-mail:
Study on subsurface damage of WC-10Co-4Cr coating in planar grinding of cup sand wheels
Xiandi SHEN1 , Chen JIANG1 , Zhenyu JIANG1, Yixuan ZHANG1, Lingqi WANG2, Guiyuan PU2
Affiliations
  • 1.School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 2.Shanghai Bearing Technology Research Institute Co., Ltd., Shanghai 201800, China
出版时间: 2025-07-15 doi: 10.16579/j.issn.1001.9669.2025.07.005
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针对磨削WC-10Co-4Cr涂层产生的亚表面损伤会导致涂层性能下降的问题,开展杯形砂轮磨削WC-10Co-4Cr涂层的亚表面损伤深度研究。根据磨削材料去除理论和压痕断裂力学,得出单颗粒磨削力理论表达式;基于杯形砂轮平面磨削特点,建立亚表面损伤深度理论预测模型;设计单因素平面磨削试验及单点抛光试验以验证模型准确性;分析不同磨削参数对工件亚表面损伤深度与表面粗糙度的影响规律。研究表明,亚表面损伤深度预测值与实测值的变化趋势一致,最大相对误差为15.8%;亚表面损伤深度及表面粗糙度随磨削深度、进给速度的增加而增加,随主轴转速的增加而减少。研究对于指导杯形砂轮磨削WC-10Co-4Cr涂层加工参数优化具有一定价值。

杯形砂轮  /  硬质合金涂层  /  单因素试验  /  单点抛光试验  /  亚表面损伤深度

The subsurface damage depth of grinding WC-10Co-4Cr coating with a cup wheel was investigated in an effort to address the issue that the subsurface damage will cause the coating's performance to deteriorate. The theoretical formula of single particle grinding force was obtained based on the principles of indentation fracture mechanics and grinding material removal theory. A theoretical subsurface damage depth prediction model was developed based on the cup wheel's surface grinding properties. The design of the single factor surface grinding test and the single point polishing test was to confirm the model's accuracy. Analysis was done on how various grinding parameters affected the workpiece's surface roughness and depth of subsurface damage. The maximum relative error is 15. 8%, and the predicted subsurface damage depth agrees with the measured value, according to the results. Surface roughness and subsurface damage depth rise with feed speed and grinding depth, but fall with spindle speed. The study has some theoretical significance for directing the process parameter optimization of cup wheel grinding of WC-10Co-4Cr coatings.

Cup wheel  /  Hard alloy coating  /  Single factor test  /  Single point polishing test  /  Subsurface damage depth
沈先弟, 姜晨, 姜臻禹, 张逸轩, 王玲奇, 普桂元. 杯形砂轮平面磨削WC-10Co-4Cr涂层亚表面损伤研究. 机械强度, 2025 , 47 (7) : 42 -48 . DOI: 10.16579/j.issn.1001.9669.2025.07.005
Xiandi SHEN, Chen JIANG, Zhenyu JIANG, Yixuan ZHANG, Lingqi WANG, Guiyuan PU. Study on subsurface damage of WC-10Co-4Cr coating in planar grinding of cup sand wheels[J]. Journal of Mechanical Strength, 2025 , 47 (7) : 42 -48 . DOI: 10.16579/j.issn.1001.9669.2025.07.005
在制造业领域,磨削作为一种广泛应用的材料去除加工过程,在提供高精度和优质表面的零件加工中扮演着不可替代的角色。然而,磨削过程中亚表面损伤问题一直是制约加工质量和效率的关键因素。亚表面损伤会导致零件强度和耐久性的下降,直接影响着零件的摩擦、润滑和密封性能。因此,深入研究磨削过程中的亚表面损伤问题,探寻影响因素,寻求优化工艺参数的方法,对于提高磨削加工的效率和质量具有重要意义。
碳化钨(WC)合金属于典型的硬脆材料,具有高硬度、优越的耐磨性和化学稳定性及较大的断裂韧性。精密磨削可以获得较好的表面质量,但依然存在缺陷,尝试通过控制加工参数来减少缺陷。LI等[1]改进了压痕断裂模型,用于描述材料磨削过程中表面粗糙度与亚表面损伤深度之间的非线性关系。向勇等[2]基于压痕断裂力学对微晶玻璃研磨加工的亚表面损伤深度进行了预测,理论值和预测值的相对误差控制在5.56%以内,模型可靠性较高。闫艳燕等[3]通过单颗磨粒的切削轨迹及其切削弧长模型,建立了纵扭超声辅助磨削氮化硅亚表面损伤深度模型并进行试验验证,预测结果与试验结果的最大相对误差为13. 38%。KLOCKE等[4]研究了不同Co含量的WC合金的材料性能,结果显示,从脆性状态到韧性状态的过渡点会改变,导致不同的磨削工艺布局。ZHANG等[5]使用尖角砂轮进行磨削试验,发现WC-Co的磨削表面主要呈现出塑性划痕的特征,表明在磨削过程中表面的Co受到挤压变形,导致WC颗粒脱落。常乐怡等[6]研究了WC粒度对WC-10Co-4Cr复合粉末表面和内部结构及其涂层的孔隙率、硬度分布和断裂韧性的影响规律,结果表明随着WC粒度的减小,涂层显微硬度提高,断裂韧性降低。
综上所述,基于压痕断裂力学的研究方法在亚表面损伤的预测方面表现得成熟且准确性较高;不同成分和粒度的碳化钨材料呈现显著的性质差异,导致加工条件和结果也会有所不同;Cr元素能提高涂层的硬度和强度,磨削WC-10Co-4Cr涂层亚表面损伤的研究鲜见。为解决这一问题,本文根据杯形砂轮平面磨削特点,由单颗粒磨削力建立了亚表面损伤深度理论预测模型,设计单因素平面磨削试验及单点抛光试验以验证模型准确性,研究不同磨削参数对WC-10Co-4Cr涂层亚表面损伤深度和表面粗糙度的影响,为优化磨削工艺参数提供依据。
为建立杯形砂轮磨削脆性材料过程中亚表面损伤(Subsurface Damage, SSD)深度的理论模型,首先必须分析静态压痕过程。在杯形砂轮磨削过程(图1)中,vs为主轴转速,vw为工件进给速度,砂轮上的磨粒可以被视为压头。图2为经典压痕断裂试验示意图[7]。当压头按压试样表面,接触载荷超过临界值时,形成3个部分:①接触点正下方的永久塑性变形区;②源自压头正下方塑性区域边界处的横向裂纹,该横向裂纹大致平行于试样表面传播;③在塑性区边界处产生并垂直扩展到试样底部的中径裂纹。图2中,CL为横向裂纹长度;Ch为横向裂纹深度;Cm为中径裂纹深度;α为压头半顶角;hi为压头进入工件的深度;b为压头所属材料塑性区半径。
LAMBROPOULOS等[8]基于压痕断裂理论和Hill模型,提出了计算中径裂纹和侧向裂纹深度的理论公式,用于描述理想孔洞扩张的过程。其中,中径裂纹深度的理论计算式为
式中,αK为无量纲数,可由αK = 0.027 + 0.090(m -1/3)计算;E为材料的弹性模量;H为材料的硬度;m为无量纲参数,一般取值在1/3∼1/2,据分析m = 1/3更为合适;α为压头半顶角,根据MAHMOUD等[9]使用扫描激光显微镜测量研磨金刚石颗粒的三维形状的结果分析,取α = 55°最合适;Fn为材料承受的单颗粒法向力;t为时刻;Kc为材料的断裂韧性。
横向裂纹深度的理论计算式为
根据试验研究发现,杯形砂轮每次磨削后,磨损仅局限在砂轮端面外侧的一部分,说明磨削过程中的磨削宽度与磨料层的宽度bs存在差异。杯形砂轮端面磨粒磨削的过程如图3所示。其中,R为磨粒绕砂轮中心的回转半径;Φ为砂轮外径;bw为工件宽度;dw为磨粒在切入和切出工件期间的移动距离;为磨粒的实际切削轨迹。dw的计算式为
因此,当dwbs时,杯形砂轮有效磨削宽度be可以视作bs,此时bs上的磨料全部起切削作用;当dw < bs时,be只能视作dw,即
实际磨削过程中,只有前半部分参与磨削,后半部分只参与摩擦,则砂轮工件之间的有效接触面积Sww,即有效磨削面积为
砂轮加工时,磨削过程中的有效磨粒数量Nd可以由磨粒表面密度C与有效接触面积Sww的乘积表示,C的值可以通过XU等[10]推导出的几何关系获得。在杯形砂轮的磨削过程中,Nd与磨削深度ap密切相关。随着ap的提高,Nd也增加;然而当ap达到一定值时,Nd将保持相对稳定。为描述这一关系,引入了一个深度因子。磨粒表面密度C的计算式为
式中,dg为金刚石颗粒的等效球形直径,可由dg =15.2M-1计算,其中M为分级筛中使用的网目尺寸,在本研究中使用的是230目的砂轮;v为金刚石在砂轮中的体积分数,本研究中使用的砂轮浓度为100,即v = 0.25。
根据压痕断裂力学以及张承龙等[11-12]的研究,当磨削过程采用脆性断裂方式去除材料时,由图2可知,单颗磨粒的材料去除体积V取决于横向裂纹的长度CL。由于CL远小于单颗粒划过的弧长L,因此可以近似看作一个长方体。CL可由文献[13]中的CL = Cm/7计算得出。
根据已有文献[14],磨屑长度可以表示为动态接触长度。但杯形砂轮平面磨削与该文献的外圆加工形式有所不同,因此将磨屑长度计算式修正为
式中,de为砂轮当量直径,de = Φ(1 + vw/vs )2
根据KALISZER[15]对磨削过程的连续性分析,在整个磨削过程中,材料的去除体积Vmr可以被视为所有Nd的累积效果,则有
式中,ε为平均路径系数,εNd成正比;Ls为最大路径,此时θ为0。
另外,从砂轮的角度分析可以得出,有效时间t内的材料去除总体积又可以表示为apbw以及dw的乘积:
从磨粒和工件的角度分析所得的材料去除体积,在理论上它们是一种等量关系[16],故有以下关系:
可以计算出单颗粒法向磨削力Fn,如式(11)。由于法向力方向是垂直工件向外,所以所有磨粒产生的力之和就是砂轮磨削时的法向磨削力Fns
式中,Kα为系列常数,由材料本身性质决定,可由式(1)~式(7)计算得出。
杯形砂轮磨削平面时始终与工件保持相同距离,故无须考虑砂轮旋转角度与最大未变形厚度的问题。磨削硬脆材料时,中径裂纹是造成亚表面损伤的主要原因,常用于表征SSD。
BIFANO等[17]指出,磨料渗入深度hi大于脆性材料的临界未变形切屑厚度hc时,磨削过程就会出现脆性断裂。hc可以通过材料的弹性模量E、硬度H和断裂韧性Kc来定量描述,其计算式为
对于杯形砂轮磨削平面的加工方式,磨粒的渗入深度hi主要由砂轮磨削深度ap决定。因此可以分为3种情况[18],如图4所示。当ap<hc时,材料去除采用韧性方式,此时没有亚表面损伤;当aphc时,材料去除方式为混合模式,既有韧性去除方式又有脆性去除方式;当aphc时,可忽略韧性去除方式,全部为脆性去除方式。由于亚表面损伤位于已加工表面之下,所以可将其表示为式(13)。在本文中,由式(12)计算为第3种情形,结合式(11)可计算出亚表面损伤深度DSSD
在DMC650V型三轴数控加工中心上开展平面磨削试验,主轴旋转精度为0.002 mm,如图5所示。试验过程中采用9257B型三向测力仪实时采集磨削力信号,计算机通过数据采集卡输入接收磨削力,随后使用Dynoware软件对其进行过滤、消除零点漂移。在课题组自行研制的磁性复合流体(Magnetic Compound Fluid, MCF)五轴抛光试验台(图6)上开展单点抛光试验,重复定位精度小于10 μm。磁流变抛光可以将需要精密成像仪器检测的裂纹深度转化为普通金相显微镜便可观察的横向裂纹,该方法不仅提高了观察亚表面裂纹的能力,还降低了检测成本。
本文平面工件尺寸为20 mm × 30 mm × 60 mm,涂层厚0.4 mm,涂层材料为WC-10Co-4Cr,基体材料为9Cr18。WC-10Co-4Cr材料的基本性能[19]表1所示。试验使用230#树脂基金刚石砂轮,具体参数由生产商给出,外径为50 mm,内径为36 mm,浓度为100%。工件固定,由杯形砂轮进行横向磨削,每组磨削前使用金刚石修整笔进行反复修整。
平面磨削试验的主要磨削参数为砂轮线速度vs、磨削深度ap、砂轮横向进给速度vw。设计单因素试验,研究不同磨削参数对亚表面损伤深度和表面粗糙度的影响规律。设计试验参数磨削深度由小到大,进给速度由慢到快,主轴转速为1 000~3 000 r/min,具体平面磨削试验方案如表2所示。为确保试验数据的可靠性,每组磨削重复3次并取平均值。由于工件相比砂轮尺寸较小,两者接触加工时间过短,每次磨削都会循环10次。
单点抛光试验中,根据前期实验室磁性复合流体抛光液的试验研究成果[20],进行抛光液的配制。考虑到涂层硬度高,故将抛光液中原成分氧化铝磨粒等量换成1 μm金刚石磨粒,具体试验方案如表3所示。为保证试验数据的可靠性,每个工件在不同位置共抛光3次并取平均值;抛光完成后在超声波浴中用乙醇清洗研磨样品15 min,使用M230-HD228S型金相显微镜观察抛光单点表面形貌,使用Taylor Hobson轮廓仪测量该点轮廓并得到亚表面损伤深度数值。
由于采用的是循环磨削,采集到的磨削力会分为不连续的10段。第一段是全程磨削,故取第一段的磨削力数据进行分析。在12.5 Hz下进行低通快速傅里叶变换(Fast Fourier Transformation, FFT)滤波处理,图7所示为S1组的磨削力曲线。选取稳定阶段的法向磨削力Fz作为Fns,任取两组数据,可得出Nd = -0.000 04ε +0.031 7。表4所示为预测值与试验值的对比结果,以相对误差和绝对误差来描述磨削力模型的准确性。
表4可知,最大相对误差为9.10%,大多数情况下具有较好的预测性能。可见,模型能有效预测磨削力的变化,有助于提高SSD预测模型的准确性和可靠性。
图8为试件经过MCF单点抛光法在显微镜400倍率下的显微图。由图8(a)~图8(c)可以看出,随着抛光深度的增加,损伤面积明显减小。在图8(d)中,大面积损伤已经基本去除,说明损伤主要集中在相对较浅的亚表面上。当抛光深度达到图8(f)所示数值时,仍然存在一些微小的缺陷无法被彻底去除。结合材料的组成与制备方法可知,这些微小的缺陷是涂层制造过程中产生的气孔[21],该气孔主要由涂层喷涂工艺决定,此时可认为亚表面损伤已经完全去除。
图9为实测值和SSD深度模型预测值的对比图。由图9可知,SSD预测值与实际检测值的变化趋势有较好的一致性,模型最大相对误差为15.8%。这说明该亚表面损伤计算方法具有一定的准确性与实用价值。预测值相较于实测值整体偏大,与磨削力预测情况类似,主要原因可能是实际参与磨削的颗粒数量比计算值少。对磨粒密度C进行计算修整或采用显微镜直接观测每单位面积的磨粒数,可有效减小模型误差。试验环境乳化液的喷射也会影响磨削力的采集,可通过调整喷射角度和压力或使用更高精度的采集卡来减小模型误差。
为了对磨削加工的工件表面质量进行评价,在实际加工质量检测环节中,常将平均算术偏差Ra作为衡量工件表面粗糙度的指标。使用Taylor Hobson表面粗糙度轮廓仪对磨削加工工件的Ra进行检测,进行多次测量取平均值,具体结果如表5所示。其中S0组所示为初始表面粗糙度。
图10所示为亚表面损伤深度与表面粗糙度-磨削深度的关系。由图10可知,随着磨削深度的增加,亚表面损伤深度与表面粗糙度也逐渐增加。这是因为增大的磨削深度直接引起了材料去除体积的增加,进而使磨粒的法向力增大,最终导致亚表面损伤深度的增加。图11所示为亚表面损伤深度与表面粗糙度-磨削深度的关系。由图11可知,随着进给速度的增加,亚表面损伤深度与表面粗糙度也随之增加。这可以用式(7)来解释,因为进给速度的增加导致磨粒切削路径增长,单位时间内去除的体积也增多,最终导致亚表面损伤深度的增加。图12所示为亚表面损伤深度与表面粗糙度-砂轮线速度的关系。由图12可知,随着主轴转速的增加,亚表面损伤深度与表面粗糙度减小。这是因为随着主轴转速的增加,切削时间减少,材料去除体积减小,从而使材料去除所需的磨削力减小,最终降低了亚表面损伤深度。
在实际加工过程中,通过模型可以预测涂层在磨削过程中可能遭受的损伤程度。在保证一定加工效率的情况下,可以通过适当减小磨削深度和进给速度、增大主轴转速来减少亚表面损伤情况,有助于提高涂层性能和寿命。
通过对杯形砂轮磨削硬质合金WC-10Co-4Cr平面涂层过程中亚表面损伤深度的研究,由单颗粒磨削材料去除理论和压痕断裂力学建立了亚表面损伤预测模型,经过单因素试验和单点抛光试验的验证,得出以下结论:
1)基于材料去除理论的磨削力模型在描述磨削力变化规律方面表现出了较高的准确性,最大相对误差为9.10%。这为理解和控制磨削力提供了可靠的基础。
2)亚表面损伤模型能够较好地预测磨削过程中的亚表面损伤深度,其最大相对误差为15.8%。这为磨削工艺的优化和质量控制提供了有效的工具。
3)不同工艺参数对亚表面损伤深度与表面粗糙度有显著影响。亚表面损伤深度与表面粗糙度随磨削深度、进给速度的增加而增大,随主轴转速的增加而减小。这为工程实践中的工艺参数选择提供一定指导。
未来的研究可以进一步优化亚表面损伤模型,以更准确地预测亚表面损伤的形成机制,在实际加工过程中有助于制定合适的磨削策略,改进磨削工艺,减小涂层损伤,提高涂层的性能,延长涂层的寿命。
  • 长三角科技创新共同体联合攻关专项2022(CSJGG1302)
  • 机械系统与振动国家重点实验室课题项目(MSV202315)
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2025年第47卷第7期
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doi: 10.16579/j.issn.1001.9669.2025.07.005
  • 接收时间:2023-11-06
  • 首发时间:2026-03-19
  • 出版时间:2025-07-15
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  • 收稿日期:2023-11-06
  • 修回日期:2023-12-19
基金
Yangtze River Delta Science and Technology Innovation Community Joint Research Project 2022(CSJGG1302)
长三角科技创新共同体联合攻关专项2022(CSJGG1302)
State Key Laboratory of Mechanical Systems and Vibration Project(MSV202315)
机械系统与振动国家重点实验室课题项目(MSV202315)
作者信息
    1.上海理工大学 机械工程学院,上海 200093
    2.上海市轴承技术研究所有限公司,上海 201800

通讯作者:

姜晨(通信作者),男,1978年生,安徽池州人,博士,教授,博士研究生导师;主要研究方向为精密加工及检测技术、制造过程智能化、微结构仿生表面设计与制造、CAM装备制造过程虚拟仿真技术;E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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