Detection of the eroding surface in the EDM process based on the current signal in the gap

To achieve a high removal rate and low electrode wear in a sinking electrical discharge machining process (EDM), rough machining parameters have to be selected according to the size of the eroding surface. In general, the size of the eroding surface varies according to the depth of the machining. Thus, it has to be determined on-line. This paper shows that the electric current signal in the gap depends on the size of the eroding surface. The significance of the process attributes of the electric current signal is established by inductive machine learning and the general decision rules are derived. The size of the eroding surface can be detected on-line by monitoring and evaluating the electric current signal in the gap.     

混粉电火花加工中粉末对工件表面的影响

对不同加工条件下混粉电火花加工后工件表面的硅含量进行了对比测量。实验结果表明：当峰值电流小于4A时，混粉电火花加工后的工件表面硅含量随峰值电流的增大而急剧减小，而当峰值电流大于4A时，工件表面硅含量随峰值电流的增大而缓慢增加；混粉电火花加工后的工件表面硅含量随脉宽的增大而增加；在其他加工条件相同的情况下，对于相同的单次放电脉冲能量，混粉电火花加工获得的工件表面硅含量随峰值电流变化的关系呈近似二次曲线。引入熵的概念，对产生上述结论的原因进行了分析，并解释了混粉电火花加工可以改善工件表面质量的机理。     

利用新型工作液和改进电极提高电火花加工性能的试验

针对电火花小孔加工中加工速度低、电极损耗严重、工件产生斜度和棱角变钝等缺陷,提出了改进小孔工具电极、研制新型工作液以提高电火花加工性能的具体措施,并在电火花机床上进行了试验。通过大量的试验研究得出:在相同的电参数下,与传统工艺相比,采用新型工作液作为介质并配有改进的电极进行电火花小孔加工时,其加工速度大幅提高、电极损耗与工件锥度有所降低,从而提高了电火花加工性能。     

半导体电火花加工爬坡式电流现象研究

对单晶硅电火花加工过程中的电流爬坡式上升现象进行了研究,结果表明,爬坡式电流主要是由加工过程中接触电阻的变化引起的,而接触电阻主要由高温区的接触面积决定。对爬坡式电流曲线的性质进行了研究,分析了温度、热导率和相变能量对接触电阻和放电电流变化的影响。最后,研究了电参数对加工效率的影响,结果表明采用大脉宽、高电压和小占空比能够大大提高加工效率。     

Numerical and experimental study on the effect of vibration of the tool in ultrasonic assisted EDM

In this paper the effect of ultrasonic vibration of the tool in the process of electrical discharge machining is investigated. The ultrasonic vibration of the tool has significant effect on the dynamic behaviour of the vapour bubble generated between the tool and the workpiece due to the electrical discharge. The computational simulation of the bubble behaviour is carried out by employing the boundary integral equation method. Results show that when the electrical discharge occurs in the closest position of the tool to the workpiece, the vapour bubble expands to the largest maximum volume of the bubble and the lifetime of the bubble is the longest. This in turn makes the pressure inside the bubble decrease rapidly to the lowest magnitude and causes melted material at the sparked point vaporize and leave the crater on the surface of the workpiece.     

基于刀轨广义偏置的电火花摇动加工补偿方法

针对电火花加工中电极摇动产生加工误差的问题,结合电极自由曲面数控加工的基本原理,提出基于数控刀轨广义偏置的补偿方法。通过对电极自由曲面原始加工刀轨的广义偏置计算,可有效、统一地解决自由曲面电极典型摇动方式所引起的加工误差问题,同时对偏置计算后产生的刀轨自交问题进行讨论。针对实际生产加工对象和不同的电极摇动方式,进行补偿计算和生产加工验证。检测结果表明,该方法能够较大地提高加工精度,缩短生产周期。     

进电端放电法对单晶硅电火花加工接触电阻的影响研究

为改善高电阻率硅的电火花线切割可加工性,提出了一种在半导体电镀金属薄膜表面放电的方法（简称进电端放电法）。首先在硅(电阻率为2.1Ω·cm)表面电镀一层铜膜,然后利用铜刷作电极,在铜膜表面进行放电,利用放电形成的高温在硅表面形成重掺杂层,以降低接触势垒。分析了表面重掺杂层的形成机理,制备了硅试件并得到了伏安曲线,结果表明,试件的进电端接触电阻明显减小。最后采用进电端放电法对电阻率为2.1Ω·cm、直径为100mm的硅锭进行电火花线切割试验,加工效率可由12mm2/min提高至30mm2/min。     

Modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al2O3+TiC mixed ceramic

Electric discharge machining (EDM) has achieved remarkable success in the manufacture of conductive ceramic materials for the modern metal industry. Mathematical models are proposed for the modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al₂O₃+TiC mixed ceramic which are developed using the response surface methodology (RSM) to explain the influences of four machining parameters (the discharge current, pulse on time, duty factor and open discharge voltage) on the performance characteristics of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The experiment plan adopts the centered central composite design (CCD). The separable influence of individual machining parameters and the interaction between these parameters are also investigated by using analysis of variance (ANOVA). This study highlights the development of mathematical models for investigating the influences of machining parameters on performance characteristics and the proposed mathematical models in this study have proven to fit and predict values of performance characteristics close to those readings recorded experimentally with a 95% confidence interval. Results show that the main two significant factors on the value of the material removal rate (MRR) are the discharge current and the duty factor. The discharge current and the pulse on time also have statistical significance on both the value of the electrode wear ratio (EWR) and the surface roughness (SR).     

基于支持向量机的电火花加工8418钢表面粗糙度预测模型

由于电火花加工过程的复杂性,单纯通过电火花加工实验方法研究各种放电参数及非电参数对工件表面粗糙度Ra的影响不但耗费大量时间,而且实验成本较高,为此基于支持向量机提出了一种适用于电火花加工表面粗糙度预测的模型。利用遗传算法对该模型中的各参数进行优化,预测不同电火花加工参数组合下的表面粗糙度;以电火花加工8418模具钢为例,将预测值与实验值进行对比,并且通过实验验证了电火花加工8418钢表面粗糙度预测模型参数的准确性;最后进行了误差分析,模型的最大误差值为2.27%。     

Effect of a pulsed electromagnetic field on the surface roughness in superfinishing EDM

It is shown and confirmed that the behaviour of a pulsed electromagnetic field influences the surface roughness especially in superfinishing electrodischarge machining (EDM). In accordance with technological experiments, instrumental measuring and theoretical analysis, some principles of the microenergy EDM process are discovered. An effective method concerning the generator and conducts is proposed to ensure that all discharges occur with desired pulse parameters. A best surface roughness of 0.04 μm R_a is achieved.     

超声振动辅助电火花微小孔加工中超声参数对加工效率的影响

利用研制的超声振动辅助电火花微小孔加工系统进行加工试验,研究了超声波激励电压的频率、幅值、脉宽与脉间对复合加工微孔的影响。为了考察加工效果,与传统电火花微孔加工试验进行了对比。试验结果表明,超声能显著改善极间工作液的循环,占空比为1/2时加工效率最高,超声激励电压、激励频率与加工时间成浴盆曲线关系,合理选择超声波参数可以有效提高加工效率。     

Investigation on the effect of EDM process variables and environments on acoustic emission signals

Abstract

The performance of electrical discharge machining (EDM) primarily depends on the spark quality generated in the inter-electrode gap (IEG) between the tool and workpiece. A method for obtaining accurate information about the spark gap is required to effectively monitor the EDM process. The rise and fall of thermal energy in the discharge zone at a rapid rate during the dielectric breakdown produces high-pressure shock waves. This work explores the suitability of using acoustic emission (AE) generated from these shock waves and the elastic AE waves released on the workpiece due to the induced stress to monitor the performance and spark gap in EDM. The information content of the AE signals acquired at various machining conditions was extracted using AE RMS, spectral energy and peak amplitude. These features were able to well discriminate the machining condition, tool material, workpiece material, flushing pressure, current density, the initial surface roughness of the tool. Additionally, the AE signal features had a good and consistent correlation with the performance parameters, including material removal rate, surface roughness (Ra and Rq) and tool wear. The findings lay the groundwork to develop an effective, non-intrusive in-situ AE-monitoring system for performance and IEG condition in EDM.     

电火花放电通道中带电粒子运动规律的研究

通过分析两极的能量分配与放电通道中带电粒子的运动之间的关系 ,采用相同电极材料的单脉冲放电方法 ,对等离子体放电通道中电子和正离子的运动规律进行了研究。结果表明在放电通道中主要是电子在运动 ,即使在大脉宽条件下放电正离子的运动也远弱于电子的运动     

模具型腔表面复合精密光整加工参数优化

利用回归方程建模的方法,建立了模具型腔表面超声电火花复合加工效果预测模型,并采用组合遗传算法实现加工参数的优化设计,给出了仿真实例,为超声电火花复合加工参数选择的可靠性和应用的可行性研究提供了新的研究方法与途径.     

电极材料对电火花加工质量影响的分析

对电火花加工中电极材料的合理选取作了详细的分析和探讨，并用实验结果分析了电极材料性能对加工质量的影响，说明了电极材料是影响电火花加工质量的一个重要因素。     

基于机器视觉的表面缺陷检测方法研究进展

在半导体、PCB、汽车装配、液晶屏、3C、光伏电池、纺织等行业中,产品外观与产品性能有着千丝万缕的联系。表面缺陷检测是阻止残次品流入市场的重要手段。利用机器视觉的技术进行检测效率高、成本低,是未来发展的主要方向。本文综述了近十年来基于机器视觉的表面缺陷检测方法的研究进展。首先给出了缺陷的定义、分类以及缺陷检测的一般步骤;然后重点阐述了使用传统图像处理方式、机器学习、深度学习进行缺陷检测的原理,并比较和分析了优缺点,其中传统图像处理方式分为分割与特征提取两个部分,机器学习包含无监督学习和有监督学习两大类,深度学习主要囊括了检测、分割及分类的大部分主流网络;随后介绍了30种工业缺陷数据集以及性能评价指标;最后指出缺陷检测方法目前存在的问题,对进一步的工作进行了展望。     

提高电火花线切割加工精度的几种因素的探讨

通过对数控快走丝电火花线切割加工原理的理解,介绍了影响线切割机床加工精度的几种因素,如:主要工艺指标、放电参数、走丝系统,工作液及其解决方案。     

基于海杂波图像的海表层流信息提取算法研究

海表层流信息提取是X波段雷达测量海浪信息的关键技术之一.为了获取实时、高精度的海表层流信息,解决目前常用算法依靠经验选取阈值精度不高、适应性差的缺点,提出了基于自适应阈值选取技术与平均加权最小二乘法的海表层流反演算法.自适应阈值选取技术能够根据图像中海浪信号的强弱不同,实现雷达图像谱中海浪信号与背景噪声的准确分离,从而最大限度地提取海浪谱,反演海表层流信息.平均加权最小二乘法考虑整体海浪谱影响,将所有的谱分量同等对待,得出测量海区的平均表层流.运用实测X波段雷达图像进行实验,结果表明改进算法的反演精度较常用算法有较大的提高.     

Suitability of CAE neural networks and FEM for prediction of wear on die radii in hot forging

Prediction of tool wear in hot die forging along the entire arbor radius by wear models known so far is a very difficult task. On these parts of tools significant changes of contact pressure and sliding lengths occur along the die curvature during the plastic flow of material formed. A new approach presented in the paper combines the use of a conditional average estimator neural network (CAE NN) with the exploitation of results obtained by the finite element method (FEM) and also data from other sources. Consequently new parameters as well as the results of experimental work can be taken into account. In this paper a brief overview of models for prediction of tool (die) wear are discussed. The theoretical background of CAE NN, as well as its application to the modeling of the tool wear phenomenon, is presented. Some results of FEM analysis of the hot forging process that serve as input parameters in the CAE NN model are also briefly discussed. Two relevant practical applications are shown. In the first example, tool wear was modeled at a higher number of strokes (blows), by knowing wear at a lower number of strokes. In the second example, the number of strokes was the output parameter—the number of strokes causing predetermined wear at any point of the tool engraving curvature (arbor radius) was predicted. A comparison between the measured and predicted values of wear demonstrated good agreement that was assessed by a corresponding coefficient of determination.     

混粉电火花加工放电点变化规律分析

借助威布尔分布理论分析了混粉电火花加工过程中微观形貌、添加粉末浓度分布对放电点变化的影响,在实验基础上观测了连续放电击穿点的相互联系;总结了混粉电火花连续放电加工中放电点位置变化的规律。结果表明:影响放电点位置变化的因素主要是粉末浓度、微观形貌和抬刀频率,而且连续放电点位置具有相关性。