基于动力学的机床加工运动分析

数控定梁龙门机床的加工精度受多种因素影响,包括零部件的制造、装配误差、材料的刚度阻尼、振动、材料切削厚度等。从提高机床加工精度出发,根据拉格朗日动力学原理建立了机床的动力学模型;分析横梁、床身等部件的自由度关系,建立了机床运动学模型;采用ADAMS软件仿真机床的瞬态动力和运动关系,对比研究了不同的瞬态切削力变化对机床切削位移、速度的影响。结果表明:当机床切削厚度增大时,切削力、切削速度和切削加速度会随之增大,同时切削速度和加速度的变化滞后切削厚度和切削力的变化;在切削受力突变处切削速度有波动,移动加速度有突变,波动时间滞后切削力突变时间。仿真结果与实际机床加工情况吻合,为机床加工的运动分析提供参考。     

基于工件表面误差的薄壁件切削力系数计算

切削力系数是计算评估机床切削力的重要参数之一.在对薄壁零件加工过程中的受力以及弹性变形进行分析的基础上,建立了基于加工零件表面误差求解切削力系数的理论模型.根据受力平衡原理,将三坐标测量的工件表面误差分配为工件和刀具弹性变形引起的误差,通过MATLAB工具代入理论模型求解切削力系数.通过将模型预测的切削力与实测切削力进行比较,结果显示模型预测的切削力波形吻合,预测切削力接近实测切削力的平均值.     

桥梁斜拉索锚具大螺距螺纹加工专用机床关键技术的研究

针对桥梁斜拉索锚具大螺距螺纹的结构特殊性,设计一台采用双层空心主轴、进行差动进给的拉索螺纹专用加工机床;研究了机床的整体方案,确定了机床的总体布局及机床参数,并设计确定机床外形尺寸、主轴、夹具等;同时根据螺纹切削力公式估算出切削力,根据切削力计算出机床的切削功率等.     

精密加工系统综合实时监测技术研究

介绍了精密加工系统综合实时监测技术。论述了对机床的振动，主轴的位移。刀具温度，刀具切削力，旋转工件温度场进行监测的原理，重点介绍了监测系统的构成，监测方法，数据采集，数据分析和应用。     

精密加工系统综合实时监测技术研究

介绍了精密加工系统综合实时监测技术.论述了对机床的振动、主轴的位移、刀具温度、刀具切削力、旋转工件温度场进行监测的原理.重点介绍了监测系统的构成、监测方法、数据采集、数据分析和应用.     

基于改进瞬时刚性力模型的机床铣削加工监测

针对用于切削力预测的瞬时刚性力模型所需参数较多且依赖初步切削实验的问题,提出一种不需要切削实验的新型切削力预测方法,实现在实际工厂中监测机床铣削加工过程。在斜角切削模型和正交切削理论的基础上,对传统的瞬时刚性力模型进行改进,减少切削力预测所需的切削参数。改进后的模型仅需在铣削操作开始时从测量的主轴电机扭矩得到的剪切角参数,无需任何额外的传感器就可以实现铣削力预测。在所提模型中,刀具跳动的影响可通过每个切削刃处的旋转半径偏差表示,以精确预测切削力。为验证该模型的有效性,进行切削实验。结果表明：切削力的预测值与实测值吻合较好,在实际加工过程中,无需任何实验铣削或任何额外的力传感器就可以准确了解机床加工状态。     

基于ADAMS的3-TPS混联机床动态特性分析

利用ADAMS软件对3-TPS型混联机床进行振动测试分析和加工仿真分析,建立了机床动态仿真分析的刚柔耦合模型,分析了机床在各个方向的振动特性,仿真分析了切削力下机床刀尖位置的位移偏差。结果表明,该机床Y、Z方向的振动响应较大,X向的响应较小;在铣削力作用下,刀尖点位移产生了明显的偏移,致使机床的加工精度降低。     

立卧进给系统多柔体模型丝杠振动仿真分析

以高精密立式和高精密卧式机床为研究对象,利用FEM技术建立高精密立式和卧式机床的进给系统刚性模型,然后利用VP技术对各零部件进行网格划分,替换刚性体,建立起进给系统多柔体模型。通过添加不同方向的切削力分别建立高精密立式和卧式机床多柔体模型。研究立式机床和卧式机床进给系统丝杠振动特性的不同,对比其在一定范围内的精确度,以选择合适的机床。论文中选择高精度的卧式机床。     

改性氧化铝陶瓷的微孔超声钻磨特性研究

本文研究了改性氧化铝陶瓷的微孔超声钻磨特性，与普通钻磨进行了比较研究，在不同的加工条件下对轴向平均切削力和扭矩进行了定量分析，并对陶瓷表面微结构进行了分析。得出普通钻磨时的轴向平均切削力和平均扭矩均远大于超声钻磨加工时的轴向平均切削力和平均扭矩；当机床主轴转速与发生器输入功率保持不变时，轴向切削力和平均扭矩随着进给量的增大而增大；当保持机床主轴转速不变且进给量比较接近时，在一定的输入功率范围内，轴向平均切削力和平均扭矩随着输入功率(相当于振幅)的增大而增大。超声加工下，磨针磨损较小；超声加工后的孔壁表面光滑。     

高速车削加工颤振稳定域建模与验证

再生颤振是制约高速车削加工效率、加工质量和刀具寿命的主要因素。以高速车削加工为研究对象,建立了考虑再生效应的高速车削动态切削力模型和颤振稳定域解析模型;通过模态实验获得机床系统的频率响应函数,在此基础上综合使用车削稳定性判据进行数值分析,获得了车削颤振稳定域解析解;进行了车削颤振稳定性时域仿真,获得了车削过程的切削力和刀具动态位移。仿真实验结果与解析解吻合良好,验证了建立的车削颤振系统动力学模型和颤振解析模型的正确性。     

In-process drill wear and breakage monitoring for a machining centre based on cutting force parameters

There are many physical parameters in the cutting process that could be used for the in-process monitoring of cutting tools' working conditions. Of these parameters, cutting forces are strongly recommended by the investigators to be used because of their higher sensitivity and more rapid response to the changes in cutting states. In this paper, the variation in the dynamic behaviour of drilling thrust force and torque with drill wear, breakage and other kinds of fault forms have been investigated experimentally. The results and associated theoretical investigations indicate that, to make the monitoring system more reliable and suitable for a wider range of cutting conditions, both thrust force F_z and torque T arising from drilling operations should be taken as associated monitoring quantities, rather than choosing just one of them. The methodology of signal signature extraction and data processing techniques are discussed and a practical monitoring strategy proposed.     

An approach based on current and sound signals for in-process tool wear monitoring

This paper presents a tool condition monitoring system (TCMS) for on-line tool wear monitoring in turning. The proposed TCMS was developed taking into account the necessary trade-off between cost and performance to be applicable in practice, in addition to a high success rate. The monitoring signals were the feed motor current and the sound signal. The former was used to estimate the feed cutting force using the least squares version of support vector machines (LS-SVM). Singular spectrum analysis (SSA) was used to extract information correlated with tool wear from the sound signal. The estimated feed cutting force and the SSA decomposition of the sound signal alone with the cutting conditions constitute the input data to the TCMS. Again LS-SVM was used to estimate tool condition and its reliability for on-line implementation was validated by experiments using AISI 1040 steel. The results showed that the proposed TCMS is fast and reliable for tool condition monitoring.     

Real time monitoring and diagnosis system development in turning through measuring a roundness error based on three-point method

A real time monitoring and diagnosis system to measure spindle center displacement (roundness error) during turning operation is introduced in this paper. The system was developed based on the three-point method. The error generated during cutting process was monitored and diagnosed by using a system equipped with a designed DSP (Digital Signal Processor) board and FFT (Fast Fourier Transform) algorithm. The system could estimate cutting force and predict other cutting characteristics such as chattering and tool wear. Using the spindle center fluctuation, i.e. a roundness error movement from the center, the relationship between the cutting force and the roundness error could also be investigated. The roundness error that eliminated geometric shape error and eccentric error from the measured signals in the frequency domain proved to be a dominating factor in determining cutting characteristics.     

Radial immersion angle estimation using cutting force and predetermined cutting force ratio in face milling

Radial immersion ratio is an important factor to determine the threshold for tool conditioning monitoring and automatic force regulation in face milling. In this paper, a method of on-line estimation of the radial immersion angle using cutting force is presented. When a tooth finishes sweeping, a sudden drop of cutting force occurs. This force drop is equal to the cutting force that acts on a single tooth at the swept angle of cut and can be obtained from the cutting force signal in feed and cross-feed directions. The ratio of cutting forces in feed and cross-feed directions acting on the single tooth at the immersion angle is a function of the immersion angle and the ratio of radial-to-tangential cutting force. In this study, it is found that the ratio of radial-to-tangential cutting force is not affected by cutting conditions and axial rake angle. Therefore, the ratio of radial-to-tangential cutting force determined by just one preliminary experiment can be used regardless of the cutting conditions for a given tool and workpiece material. Using the measured cutting force during machining and a predetermined ratio, the radial immersion ratio is estimated in the process. Various experiments show that the radial immersion ratio and instantaneous ratio of the radial to tangential direction cutting force can be estimated very well by the proposed method.     

Three-axial cutting force measurement in micro/nano-cutting by utilizing a fast tool servo with a smart tool holder

Cutting force is a significant indicator for in-process monitoring of cutting status. Although dynamometers are widely used in cutting force measurement, they are not suitable for nano-cutting due to insufficient sensitivities and low integrating possibilities. This paper presents a smart tool holder composed by piezoelectric ceramics and a flexible hinge, which could be integrated with a fast tool servo (FTS), for three-axial cutting force measurements in micro/nano-cutting. An algorithm was developed for enabling its quasi-static force measurement. Experiments were performed to verify the capabilities of cutting force measurement, demonstrating a high measurement sensitivity for indicating the micro/nano-cutting status.     

Tool wear monitoring and breakage detection based on “intelligent filtering”

Several physical quantities can be used for indirect tool wear monitoring and breakage detection. Cutting forces are appropriate, since they determine the suitability of a tool for cutting. However, disturbances make the accurate and fast tool condition monitoring based upon force analysis difficult. To eliminate disturbances averaging or filtering within a predetermined bandwidth has often been applied. A new method of decomposing the force signal into components having close relationships with physical phenomena taking place during cutting is presented. The term “intelligent filtering” denotes decomposition based on on-line identification of model(s) of the cutting process. Application of “intelligent filtering” for the milling process with two cutting insert tools is discussed.     

On-line monitoring of depth of cut in AWJ cutting

Monitoring of the abrasive waterjet (AWJ) cutting process has become increasingly important. The present paper proposes a model for on-line depth of cut monitoring based on the acoustic emission (AE) response to the variation in AWJ depth of cut, instead of the expensive and impractical vertical cutting force monitoring. The main objective is to use the AE technique in order to predict the actual depth of cut in AWJ cutting under normal cutting conditions. It was found that the root mean square of the acoustic emission energy (AErms) increases linearly with an increase in the depth of cut and could be used for its on-line monitoring. The results show that the AE is the most suitable technique for AWJ monitoring, as the AE signal has high sensitivity to the variation in the depth of cut.     

Effects of tool flank wear on orthogonal cutting process of aluminum alloy

The tool flank begins to wear out as soon as cutting process proceeds. Cutting parameters such as cutting forces and cutting temperature will vary with increasing degree of flank wear. In order to reveal the relationship between them, the theoretical situations of cutting process were analyzed considering the tool flank wear effect. The variation rules of cutting force, residual stress and temperature distributions along with the tool flank wear were analyzed comparing with the sharp tool tip. Through FEM simulation method, affections of the tool flank wear value VB on cutting forces, residual stress and temperature distributions were analyzed. A special result in this simulation is that the thrust force is more sensitive to tool flank wear, which can be used as a recognition method of tool condition monitoring. The FEM simulation analysis result agrees well with the experimental measuring data in public literatures and some experiments made also by the authors.     

铣削过程中基于伺服电流信号的切削力监测

刀具破损和刀具磨损的自动检测是数控机床自动加工中的一个重要环节。基于伺服电机电流的切削力监控是一个有效的无传感器方法,该方法的关键是如何从伺服电流信号中准确提取切削刃的力波动表征信号。在对伺服电流信号进行时域、频域分析的基础上,基于可变加工参数给出实时提取切削刃力波动表征信号的方法,并通过相关实验验证了该方法的合理性。