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The effect of TWD estimation error on the geometry of machined surfaces in micro-EDM milling

机译:TWD估计误差对微细电火花加工中加工表面几何形状的影响

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摘要

In micro EDM (electrical discharge machining) milling, tool electrode wear must be effectively compensated in order to achieve high accuracy of machined features [1]. Tool wear compensation in micro-EDM milling can be based on off-line techniques with limited accuracy such as estimation of the volumetric wear ratio and continuous compensation proportional to the in-plane displacements (anticipated wear compensation) or real time wear sensing [2]. Tool wear per discharge (TWD) is a parameter based on which a novel approach has been developed for tool wear compensation based on discharge counting and statistical characterization of the discharge population [3]. The TWD based approach permits the direct control of the position of the tool electrode front surface. However, TWD estimation errors will generate a self-amplifying error on the tool electrode axial depth during micro-EDM milling. Therefore, accuracy of the tool wear compensation method as well as the geometry of the machined feature depends on the variability of TWD during machining operation. This paper analyses the effect of errors on the estimation of TWD on geometry of the machined features, in the case of a typical slot machining process. The error propagation effect is demonstrated through a software simulation tool developed by the authors for determination of the correct TWD for subsequent use in compensation of electrode wear in EDM milling. The implemented model uses an initial arbitrary estimation of TWD and a single experiment with determination of number of discharges and removed electrode volume. The simulation tool developed is used to calculate the effects of errors in the initial estimation of TWD on the propagation effect of error on the depth of the cavity generated. Simulations were applied to EDM milling of a slot of 5000 μm length and 50 μm depth, with a segment length of 100 μm and layer thickness of 1 μm. Simulations have been performed for TWD estimation errors ranging from -15% to +15%, see Figure 1: a. In order to validate the results obtained using simulations, slot milling experiments were performed on a SARIX SX-200 micro-EDM machine. Tungsten carbide rod of Ø300 μm and Stavax steel blocks were used as the tool material and workpiece material respectively. The programming for machining along the segments and along each layer was done using G codes. The population of discharge current signals were characterized forselection of the trigger level to count all the discharges contributing to the tool wear. Experimentswere replicated five times to ensure the repeatability of the results. From the simulations, it isobserved that the depth error due to TWD estimation error is magnified and transmitted in differentprogressions along the tool path. The simulation results show that a variation in TWD estimation errorfrom +1% to +5%, the maximum error in the geometry of micro-EDM milled profile varied from +6.14%to +40.52%. It is observed that results of depth predicted using the simulation and the average depthobtained using experiments match thoroughly within an error of 5%, see Figure 1: b.
机译:在微型EDM(电火花加工)铣削中,必须有效地补偿工具电极的磨损,以便获得较高的加工特征精度[1]。微型EDM铣削中的刀具磨损补偿可以基于精度有限的离线技术,例如,估算体积磨损率和与面内位移成比例的连续补偿(预期磨损补偿)或实时磨损感测[2] 。每次放电的刀具磨损(TWD)是一个参数,基于该参数,已开发出一种基于放电计数和放电总体统计特征的刀具磨损补偿的新方法[3]。基于TWD的方法允许直接控制工具电极前表面的位置。但是,TWD估计误差将在微型EDM铣削过程中在工具电极轴向深度上产生自放大误差。因此,刀具磨损补偿方法的精度以及加工特征的几何形状取决于加工操作期间TWD的可变性。在典型的槽加工过程中,本文分析了误差对TWD估计值对加工特征几何形状的影响。作者开发的软件仿真工具可证明误差传播的影响,该软件仿真工具可用于确定正确的TWD,以便随后用于补偿EDM铣削中的电极磨损。所实现的模型使用TWD的初始任意估计和确定放电次数和去除电极体积的单个实验。开发的仿真工具用于计算TWD的初始估计中的误差对误差对生成的腔体深度的传播效应的影响。将模拟应用于长度为5000μm,深度为50μm,段长为100μm,层厚度为1μm的缝的EDM铣削。对TWD估计误差的仿真范围为-15%至+ 15%,请参见图1:a。为了验证使用模拟获得的结果,在SARIX SX-200 micro-EDM机床上进行了槽铣实验。 Ø300μm的碳化钨棒和Stavax钢块分别用作工具材料和工件材料。沿段和沿每一层进行加工的编程是使用G代码完成的。表征放电电流信号,以选择触发电平,以计算所有导致工具磨损的放电。实验重复了五次,以确保结果的可重复性。从仿真中可以看出,由于TWD估计误差引起的深度误差被放大并沿刀具路径以不同的进度传输。仿真结果表明,TWD估计误差在+ 1%到+ 5%之间变化,微型EDM铣削轮廓的几何形状的最大误差在+ 6.14%到+ 40.52%之间变化。可以观察到,使用模拟预测的深度结果和使用实验获得的平均深度在5%的误差内完全匹配,请参见图1:b。

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