刀具磨损自动识别及检测系统

对加工状态下刀具磨损值及时有效的检测,可以在保证加工精度的前提下提高加工效率,同时为刀具剩余寿命预测提供有力的数据支撑。针对刀具磨损值测量过程中人工参与的不足、易受主观因素影响、检测精度低等问题,建立了刀具磨损图像自动检测系统,基于最大类间方差及遗传算法迭代寻找最佳阈值,进行磨损区域分割;利用磨损区域呈现“线状”的特点,进行磨损区域特征识别及滤波;基于多级Hough变换以及磨损区域二次识别的方法,将刀具磨损区域在图像中清晰地提取出来。在此基础上,基于Canny算子边缘检测方法建立刀具磨损曲线,计算出磨损区域的磨损值。在刀具磨损检测系统计算的磨损量与超景深显微镜的人工测量结果进行比对,经实验表明,该磨损检测系统检测误差在±6%以内,并且提高了刀具磨损值的检测效率。

考虑应变-温度耦合与高温动态结晶的钛合金本构模型研究

Ti-6Al-4V合金的高速切削加工是一个复杂的高温高应变率的热力耦合过程,为更加准确研究Ti-6Al-4V合金在高温高应变率下的真实应力-应变关系,构建了一种修正Johnson-Cook(J-C)本构模型。修正的J-C本构模型综合考虑了塑性阶段应变硬化率会随加载温度的升高而降低的现象,以及在达到高温动态结晶效应的临界温度时,Ti-6Al-4V合金的流动应力会急剧下降的现象。基于修正J-C本构模型的流动应力-应变预测结果与试验数据吻合程度良好,误差率在8%以内,准确的反映了Ti-6Al-4V合金在不同加载温度下的真实应力-应变关系。

双转台五轴数控机床主轴热误差测量与建模

为了测量数控机床实际切削加工过程中主轴的热误差,并优化热误差模型的输出,提出利用热测试件测量机床主轴热误差的方法,并利用误差特性分离出热误差。针对机床热误差建模中温度测点优化选择的问题,提出基于K-means++算法和相关系数法相结合的方法选取温度敏感点,采用K-means++算法对所有温度测点进行聚类,相关系数法计算各个温度变量与主轴热误差之间的相关性,从而确定温度敏感点,结合分离出的热误差建立主轴热误差多元线性回归模型。在VMC-C50双转台五轴数控机床上对该方法进行试验验证,结果表明,温度测点的数量由8个减少为2个,模型的预测精度及鲁棒性得到有效提升。

变分模态分解与稀疏SURE的电子图像噪声抑制

为解决电子微结构图像在摄取、传输或存储的过程中易被外界噪声干扰、图像保真度差的问题,提出了一种变分模态分解与稀疏Stein无偏风险估计(Stein unbiased risk estimator,SURE)相结合的图像噪声抑制方法,以铝合金、双相钢与钛合金Ti6Al4V 3种材料的电子背散射衍射图像为例.首先,在已采集的电子背散射衍射图像中加入高斯噪声与Speckle斑纹噪声来模拟被干扰图像;然后,利用变分模态分解方法按照频率尺度将含噪模拟图像分解为固有特征成分与高频噪声成分;继而利用Haar小波冗余字典对固有特征成分进行稀疏表示,在一阶可导收缩函数的基础上推导了稀疏Stein无偏风险估计阈值选择的优化目标函数,最后,利用黄金分割搜索法计算得到全局最佳自适应阈值.结果表明:提出的方法可有效去除外界干扰噪声,提高了图像的峰值信噪比;以铝合金为例,当噪声标准差为30时,提出方法的图像峰值信噪比突破了单一稀疏SURE收缩曲线的最大值,比Neigh-Shrink方法高0.39 dB,比KSVD方法高2.895 dB,比小波阈值去噪算法高3.07 dB.

深度学习与多信号融合在铣刀磨损状态识别中的研究

为精确地识别刀具磨损状态,提出了一种深度学习与多信号融合相结合的识别方法。以自编码网络为基础,构建了堆叠稀疏自编码网络。采集铣刀不同磨损状态下的力信号、振动信号及声发射信号,并对上述信号进行小波包分解以便获取能够表征铣刀磨损的时频域特征。利用无监督学习和有监督学习对堆叠稀疏自编码网络进行训练,建立了深度学习的铣刀磨损状态识别模型。研究结果表明,多信号融合的深度学习模型对铣刀磨损状态识别准确率达到94.44%。

轴向超声振动辅助铣削力的建模与实验研究

轴向超声振动辅助铣削工艺是近年来铣削领域的最新进展之一,目前对于轴向超声振动铣削力建模的研究相对较少。针对这一问题,提出了一个考虑轴向振动的超声铣削力建模方法。根据空间中刀尖运动轨迹的坐标,建立了准确的瞬时切厚模型,得到不同切削角度下切屑形成力和摩擦力模型。将铣削力与未变形的切屑截面面积建立函数关系,考虑了瞬时未变形切厚模型以及瞬时切深模型,得到了轴向冲击力模型。结合切屑形成力模型、摩擦力模型和轴向冲击力模型得到轴向超声振动辅助铣削力模型。研究结果表明:预测的铣削力变化趋向与实验测得的铣削力变化趋向吻合,最大峰值力的误差范围在7.53%~17.35%之间。本文结果将为超声振动辅助铣削工艺的优化研究提供理论基础。

Numerical simulation of thermal field of FSW 2219 aluminum alloy thick plate

To investigate the influence of temperature field of friction stir welding(FSW)2219 aluminum alloy thick plate,and to achieve effective prediction of temperature field,the authors establish a three-dimensional numerical simulation model of FSW 18 mm thick 2219 aluminum alloy based on ABAQUS/CEL,considering the morphological characteristics of the tool pin.The simulations of plunging,dwelling,and welding stages are achieved.The distribution of temperature and temperature cycle curve of characteristic points in welding process are obtained.The validity of the simulation results is verified by experiments.The influence of the tool-rotational speed and welding speed on temperature field is explored.The work lays a foundation for the prediction and control of temperature field in FSW medium thickness 2219 aluminum alloy,and provides reference for selection of welding parameters to ensure high quality welding of fuel tank of heavy-lift rocket.

Research on Surface Roughness of Supersonic Vibration Auxiliary Side Milling for Titanium Alloy

The processed surface contour shape is extracted with the finite element simulation software.The difference value of contour shape change is used as the parameters of balancing surface roughness to construct finite element model of supersonic vibration milling in cutting stability domain.The surface roughness trial scheme is designed in the orthogonal test design method to analyze the surface roughness test result in the response surface methodology.The surface roughness prediction model is established and optimized.Finally,the surface roughness finite element simulation prediction model is verified by experiments.The research results show that,compared with the experiment results,the error range of the finite element simulation model is 27.5%–30.9%,and the error range of the empirical model obtained by the response surface method is between 4.4%and 12.3%.So,the model in this paper is accurate and will provide the theoretical basis for the optimization study of the auxiliary milling process of supersonic vibration.

Constitutive modeling of ultra?fine?grained titanium flow stress for machining temperature prediction

This work investigates the machining temperatures of ultra-fine-grained titanium(UFG Ti),prepared by equal channel angular extrusion,through analytical modeling.UFG Ti has great usefulness in biomedical applications because of its high mechanical strength,sufficient manufacturability,and high biocompatibility.The temperatures were predicted using a physics-based predictive model based on material constitutive relation and mechanics of the orthogonal cutting process.The minimization between the stress calculated using Johnson–Cook constitutive model and the same stress calculated using mechanics model yields the estimation of machining temperatures at two deformation zones.Good agreements are observed upon validation to the values reported in the literature.The machinability of UFG Ti is investigated by comparing its machining temperature to that of Ti–6Al–4V alloy under the same cutting conditions.Significantly lower temperatures are observed in machining UFG Ti.The computational efficiency of the presented model is investigated by comparing its average computational time(~0.5 s)to that of a widely used modified chip formation model(8900 s)with comparable prediction accuracy.This work extends the applicability of the presented temperature model to a broader class of materials,specifically ultra-fine-grained metals.The high computational efficiency allows the in situ temperature prediction and optimization of temperature condition with process parameters planning.

Conventional and micro scale finite element modeling for metal cutting process:A review

The metal cutting process is accompanied by complex stress field,strain field,temperature field.The comprehensive effects of process parameters on chip morphology,cutting force,tool wear and residual stress are complex and inter-connected.Finite element method(FEM)is considered as an effective method to predict process variables and reveal microscopic physical phenomena in the cutting process.Therefore,the finite element(FE)simulation is used to research the conventional and micro scale cutting process,and the differences in the establishment of process variable FE simulation models are distinguished,thereby improving the accuracy of FE simulation.The reliability and effectiveness of FE simulation model largely depend on the accuracy of the simulation method,constitutive model,friction model,damage model in describing mesh element,the dynamic mechanical behavior of materials,the tool-chip-workpiece contact process and the chip formation mechanism.In this paper,the FE models of conventional and micro process variables are comprehensively and up-to-date reviewed for different materials and machining methods.The purpose is to establish a FE model that is more in line with the real cutting conditions,and to provide the possibility for optimizing the cutting process variables.The development direction of FE simulation of metal cutting process is discussed,which provides guidance for future cutting process modeling.

薄壁件铣削过程加工变形研究进展

机床加工性能和刀具切削性能的发展使得薄壁件的高效率和高精密加工成为可能,也使得薄壁件在航空航天领域得到更广泛应用。薄壁零件结构复杂、刚度低,在铣削过程中易发生变形,因此精准预测与控制薄壁件的加工变形是机加工领域亟需解决的工艺难题。通过对薄壁件分类以及加工工艺分析,归纳总结引起薄壁件加工变形的因素,对加工变形影响最为关键的铣削力计算模型进行简述;结合国内外薄壁件变形预测与控制方法的研究,以弹塑性和数值模拟方法对薄壁件加工变形进行预测,通过加工工艺优化、辅助支撑技术、高速切削技术和数控补偿技术等方法对薄壁件加工过程的变形量进行控制;基于数据驱动数字孪生体的更新迭代,实现薄壁件实际加工过程的孪生及薄壁件变形预测与控制,构建了以数字孪生为平台的薄壁件加工变形预测与控制理论框架;最后对数字孪生在薄壁件加工变形预测及控制的发展与应用提出展望。

An iterative blending integrating grinding force model considering grain size and dislocation density evolution

The dynamic force load in grinding process is considered as a crucial factor affecting the quality of parts,and a better understanding of the mechanism of force generation is conducive to revealing the evolution of material microstructure more precisely.In this study,an iterative blending integrating grinding force model that comprehensively considers the impact of grain size and dislocation density evolution of the material is proposed.According to the grinding kinematics,the interaction of grit-workpiece is divided into rubbing,plowing,and chip formation stages in each grinding zone.On this basis,the evolution of material microstructure in the current chip formation stage will affect the rubbing force in the next grinding arc through flow stresses,which in turn will influence the total grinding force.Therefore,the flow stress models in rubbing and chip formation stages are firstly established,and then the dislocation density prediction model is established experimentally based on the characteristics of grain size.The effects of the evolution of grain size and dislocation density on the grinding forces during the grinding process are studied by means of iterative cycles.The results indicate that the implementation of an iterative blending scheme is instrumental in obtaining a higher accurate prediction of the grinding force and a deeper insight of the influence mechanisms of materials microstructure on grinding process.

钛合金铣削过程刀具前刀面磨损解析建模

钛合金Ti6Al4V作为典型的航空航天难加工材料,在其铣削过程中硬质合金刀具的磨损会降低加工过程稳定性,进而影响加工效率和已加工表面表面质量。刀具前刀面磨损会导致刀具刃口强度降低,并影响切屑的流向和折断情况。针对前刀面磨损机理进行分析并构建了月牙洼磨损深度预测模型。首先运用解析方法构建了前刀面应力场模型,得到切屑在前刀面滑动过程中的刀具前刀面应力分布情况及磨损位置。基于刀-屑接触关系的基础上建立了前刀面温度场模型。然后,基于所得刀具前刀面应力与温度分布,构建综合考虑磨粒磨损、粘结磨损与扩散磨损的铣刀月牙洼磨损深度预测模型,获得月牙洼磨损预测曲线;结合铣刀月牙洼磨损带沿切削刃方向分布的特点,建立了随时间变化的铣刀前刀面磨损体积预测模型。最后通过试验验证了切削宽度对前刀面磨损的影响规律,预测结果与试验测量值具有较好的吻合性。结果表明随着切削宽度的增加,月牙洼磨损深度及前刀面磨损体积都随之增加。研究结果为钛合金铣削用刀具的设计和切削参数的合理选择提供了理论基础。

干切削温度场的数学物理建模与预测验证

针对正交干切削加工过程,建立了刀具与切屑接触区域温度场数学物理模型。模型采用绝热半无限介质热源叠加的方法,计算出切屑剪切变形区和"刀具-切屑"摩擦区叠加影响下刀具与切屑在接触区的温度场,分析了最高温度产生位置及其机理。基于该模型,对锋利PCBN刀具硬车削轴承钢过程的温度场进行预测,得到的刀具与切屑接触面温度在多个切削速度条件下误差均小于8%,说明该模型能够实现对锋利切削加工温度场的精确预测。

A review of chatter vibration research in milling

Chatter is a self-excited vibration of parts in machining systems. It is widely present across a range of cutting processes, and has an impact upon both efficiency and quality in production processing. A great deal of research has been dedicated to the development of technologies that are able to predict and detect chatter. The purpose of these technologies is to facilitate the avoidance of chatter during cutting processes, which leads to better surface precision, higher productivity,and longer tool life. This paper summarizes the current state of the art in research regarding the problems of how to arrive at stable chatter prediction, chatter identification, and chatter control/-suppression, with a focus on milling processes. Particular focus is placed on the theoretical relationship between cutting chatter and process damping, tool runout, and gyroscopic effect, as well as the importance of this for chatter prediction. The paper concludes with some reflections regarding possible directions for future research in this field.