数控铣削加工曲面时刀具轨迹的研究

数控铣削加工曲面过程中,刀具的运动轨迹是影响加工质量的一个重要因素.研究了数控铣削加工过程中刀具轨迹的生成,以及不同轨迹形式对加工质量有何影响等内容.     

A new method for cutting force prediction in peripheral milling of complex curved surface

The instantaneous uncut chip thickness and entry/exit angle of tool/workpiece engagement vary with tool path, workpiece geometry and cutting parameters in peripheral milling of complex curved surface, leading to the strong time-varying characteristic for instantaneous cutting forces. A new method for cutting force prediction in peripheral milling of complex curved surface is proposed in this paper. Considering the tool path, cutter runout, tool type(constant/nonconstant pitch cutter) and tool actual motion, a representation model of instantaneous uncut chip thickness and entry/exit angle of tool/ workpiece engagement is established firstly, which can reach better accuracy than the traditional models. Then, an approach for identifying of cutter runout parameters and calibrating of specific cutting force coefficients is presented. Finally, peripheral milling experiments are carried out with two types of tool, and the results indicate that the predicted cutting forces are highly consistent with the experimental values in the aspect of variation tendency and amplitude.     

Model-based identification of tool runout in end milling and estimation of surface roughness from measured cutting forces

This paper presents a model-based approach for the identification of tool runout and the estimation of surface roughness from measured cutting forces. In the first part of the paper, the effect of tool runout on variations in the cutting forces and the effect on surface roughness generation are studied. Thereby, several influencing parameters are identified and examined systematically. Based on theoretical considerations, systematic relationships between tool runout, resultant process force variations, and surface roughness characteristics are deduced. The sensitivity of process force variation is investigated for varying runout parameters by experimental tests. In the next part, the model-based runout identification method is developed, which identifies runout parameters accurately from the measured process forces. The approach has been tested extensively and was verified by measured runout parameters and the correlation of surface roughness characteristics of the machined workpiece. The performance of the developed approach is demonstrated in the final part by comparing the result of the model-based surface reconstruction with the measured surface topography.     

数控铣削加工中刀具半径补偿问题研究

刀具半径补偿是数控铣削加工中的常用功能，就数控铣削加工中刀具半径补偿的建立和取消、刀具半径补偿量的指定和计算方法、刀具半径补偿功能的应用进行了研究。     

Simulation of multicutter milling with tool vibration

Simulation of multitooth milling reveals the shortcomings of current CAM systems. An example illustrates the potential for expanding CAM systems so as to take account of vibration in developing the control software for numerically controlled machine tools.     

基于五轴数控机床的膝关节复杂曲面高效加工策略

研究了基于PowerMILL软件的刀具路径优化和数控机床高效加工策略,对直线投影精加工策略中的螺旋、圆形和线性三种样式加工的特点进行了分析,找到最优样式,并在加工膝关节的过程中进行了应用和验证。     

Simulation tool for prediction of cutting forces and surface quality of micro-milling processes

The improvement of micro-milling processes implies the application of advanced analysis and modeling techniques to derive a deeper process understanding. Because of micro-scale effects, monitoring, and measurement systems applied in conventional milling are in most cases not suitable for identifying optimal cutting conditions. Therefore, analytical and mechanical models have been developed in recent years to account for impact factors dominating the micro-milling errors. Within the research presented in this publication, geometric, kinematic, and dynamic models have been adjusted and dimensioned according to the dominating impact factors in micro-milling and have been consolidated to enable for a time-domain simulation. The effect of element size of discretized workpiece and tool as well as the time step size on cutting forces has been evaluated. The accuracy of predicting cutting forces has been investigated and a good agreement of measured and simulated cutting forces has been found. Finally, a mold for a micro-fluidic device has been machined virtually and experimentally to evaluate the accuracy of the integrated models in predicting the final quality of a micro-milled part in terms of surface quality parameters.     

金刚石刀具刃磨装夹系统的振动特性分析

在金刚石刀具的刃磨过程中,机床本身及其刃磨装夹系统的振动干扰会直接影响到刀具的锋锐度和表面粗糙度。本文通过对刃磨过程特征振动信号的分析,结合模态实验,对刃磨装夹系统结构的振动特性进行了分析和评价。     

Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling

Influence of tool geometry on the quality of surface produced is well known and hence any attempt to assess the performance of end milling should include the tool geometry. In the present work, experimental studies have been conducted to see the effect of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the machining performance during end milling of medium carbon steel. The first and second order mathematical models, in terms of machining parameters, were developed for surface roughness prediction using response surface methodology (RSM) on the basis of experimental results. The model selected for optimization has been validated with the Chi square test. The significance of these parameters on surface roughness has been established with analysis of variance. An attempt has also been made to optimize the surface roughness prediction model using genetic algorithms (GA). The GA program gives minimum values of surface roughness and their respective optimal conditions.     

Investigating the cutting phenomena in free-form milling using a ball-end cutting tool for die and mold manufacturing

This paper presents an investigation of nonplanar tool-workpiece interactions in free-form milling using a ball-end cutting tool, a technique that is widely applied in the manufacturing of dies and molds. The influence of the cutting speed on the cutting forces, surface quality of the workpiece, and chip formation was evaluated by considering the specific alterations of the contact between tool-surface along the cutting time. A trigonometric equation was developed for identifying the tool-workpiece contact along the toolpath and the point where the tool tip leaves the contact with the workpiece. The experimental validation was carried out in a machining center using a carbide ball-end cutting tool and a workpiece of AISI P20 steel. The experimental results demonstrated the negative effect of the engagement of the tool tip into the cut on machining performance. The length of this engagement depends on the tool and workpiece curvature radii and stock material. When the tool tip center is in the cut region, the material is removed by shearing together with plastic deformation. Such conditions increase the cutting force and surface roughness and lead to an unstable machining process, what was also confirmed by the chips collected.     

Mechanistic modelling of the milling process using complex tool geometry

Mechanistic models of the milling process must calculate the chip geometry and the cutter edge contact length in order to predict milling forces accurately. This task becomes increasingly difficult for the machining of three dimensional parts using complex tool geometry, such as bull nose cutters. In this paper, a mechanistic model of the milling process based on an adaptive and local depth buffer of the computer graphics card is compared to a traditional simulation method. Results are compared using a 3-axis wedge shaped cut – a tool path with a known chip geometry – in order to accommodate the traditional method. Effects of cutter nose radius on the cutting and edge forces are considered. It is verified that there is little difference (1.4% at most) in the predicted force values of the two methods, thereby validating the adaptive depth buffer approach. The numerical simulations are also verified using experimental cutting tests of aluminium, and found to agree closely (within 12%).     

Novel tool wear monitoring method in ultra-precision raster milling using cutting chips

Tool wear monitoring is a popular research topic in the field of ultra-precision machining. However, there appears to have been no research on the monitoring of tool wear in ultra-precision raster milling (UPRM) by using cutting chips. In the present research, monitoring tool wear was firstly conducted in UPRM by using cutting chips. During the cutting process, the fracture wear of the diamond tool is directly imprinted on the cutting chip surface as a group of ‘ridges’. Through inspection of the locations, cross-sectional shape of these ridges by a 3D scanning electron microscope, the virtual cutting edge of the diamond tool under fracture wear is built up. A mathematical model was established to predict the virtual cutting edge with two geometric elements: semi-circle and isosceles triangle used to approximate the cross-sectional shape of ridges. Since the theoretical prediction of cutting edge profile concurs with the inspected one, the proposed tool wear monitoring method is found to be effective.     

复杂形状工件的端铣切削力模型

以传统的端铣切削力模型为基础，提出了一种新的端铣加工中静态切削力的预报模型。该模型考虑了复杂的工件形状和不同的铣刀进给轨迹。给出了一种新的工件和铣刀接触算法。     

Optimal cutting condition determination for desired surface roughness in end milling

CNC end milling is a widely used cutting operation to produce surfaces with various profiles. The manufactured parts’ quality not only depends on their geometries but also on their surface texture, such as roughness. To meet the roughness specification, the selection of values for cutting conditions, such as feed rate, spindle speed, and depth of cut, is traditionally conducted by trial and error, experience, and machining handbooks. Such empirical processing is time consuming and laborious. Therefore, a combined approach for determining optimal cutting conditions for the desired surface roughness in end milling is clearly needed. The proposed methodology consists of two parts: roughness modeling and optimal cutting parameters selection. First, a machine learning technique called support vector machines (SVMs) is proposed for the first time to capture characteristics of roughness and its factors. This is possible due to the superior properties of well generalization and global optimum of SVMs. Next, they are incorporated in an optimization problem so that a relatively new, effective, and efficient optimization algorithm, particle swarm optimization (PSO), can be applied to find optimum process parameters. The cooperation between both techniques can achieve the desired surface roughness and also maximize productivity simultaneously.     

铣刀磨损量监测和剩余寿命预测方法研究

研究在线诊断端面铣刀磨损量和预测铣刀剩余寿命的方法。首先通过实验采集Y向铣削力作为监测信号,分析铣削力与刀具磨损量VB和刀具磨损时间之间的关系。然后,通过铣削力信号分析提取出有效监测特征向量,此特征向量作为BP神经网络的输入,用于刀具磨损量的监测和剩余寿命的预计。最后,通过实验证明,该神经网络模型误差很小,利用该方法能够正确地进行在线监测和预测。