利用神经网络建立电火花加工工艺模型

以峰值电流、脉冲宽度、脉冲间隔、抬刀时间和加工时间为输入参数,以加工速度和表面粗糙度为输出参数,利用人工神经网络技术建立了电火花加工工艺模型。经过与实验数据的比较,认为该模型能精确地预测出给定条件下的加工速度和表面粗糙度,真实反映了机床的加工工艺规律。     

EDM放电间隙检测及工作参数选择研究

对基于间隙平均电压检测法的放电间隙状态检测进行了理论分析,经Pspice电路仿真模拟电压检测过程,验证了间隙平均电压检测法应用于伺服控制信号电压检测的可行性,并在此基础上,对电火花成型加工脉冲电源电参数的选择提出了几点选择标准。     

EDM放电间隙检测及工作参数选择研究

对基于间隙平均电压检测法的放电间隙状态检测进行了理论分析,经Pspice电路仿真模拟电压检测过程,验证了间隙平均电压检测法应用于伺服控制信号电压检测的可行性,并在此基础上,对电火花成型加工脉冲电源电参数的选择提出了几点选择标准.     

响应面法优化SKD11电火花线切割工艺参数研究

针对高耐磨韧性通用冷作模具钢SKD11的难加工性,利用基于响应面法的中心复合设计电火花线切割工艺参数对材料去除率的影响规律,建立二阶响应面模型,以最大材料去除率为目标优化电火花线切割工艺参数。结果显示:脉冲放电时间、脉冲间隙时间、电流峰值对材料去除率的影响显著,伺服电压对材料去除率的影响较小,最优工艺参数组合为:脉冲放电时间T_(on)为14μs、脉冲间隙时间T_(off)为20μs、电流峰值I_P为4. 5 A和伺服电压S_V为5 V。     

超短脉冲激光器加工工艺参数自适应及其生效技术

为了解决超短脉冲激光数控加工中激光参数与加工速度等参数不匹配导致的加工宽度与加工深度过大或过小的问题,分别从作用机理推导、加工工艺参数内在规律探寻角度建立了基于激光参数及加工速度表示的加工宽度和加工深度表达式,进而建立超短脉冲激光器加工工艺参数求解模型。在基于UMAC的开放式数控系统基础上,针对加工速度匀速和变速两种情况,分别给出了超短脉冲激光器加工工艺参数自适应及生效的技术方案。通过仿真实验,验证了超短脉冲激光器加工工艺参数求解模型的预测性能,其对数控情境下超短脉冲激光器加工工艺参数自适应的相关研究工作,以及提高加工工艺实验效率、降低成本等均具有参考价值。     

灰色模型电火花磨削蜂窝环的试验研究

以电火花磨削蜂窝环(GH3536)为试验对象,设计出L16(44)正交表。采用灰色关联分析方法研究峰值电流、峰值电压、脉冲宽度、脉冲间隔四个主要电加工参数对加工速度的影响关系,基于GM(1,N)多变量灰色模型及人工神经网络原理建立电火花磨削蜂窝环的加工速度预测模型,并在MATLAB环境下进行仿真,得出模型在样本参数范围内的绝对均值误差为0.53%,在样本参数外的绝对均值误差为6.74%。结果表明该模型能映射出电火花磨削蜂窝环的工艺规律并能成功预测出其加工速度,为电火花磨削蜂窝环工艺参数的选择提供了参考和依据,具有实用意义。     

基于神经网络的电火花加工工艺选择模型研究

针对电火花加工工艺数据的特点,研究了神经网络输入输出数据的预处理方法,提出了基于对数变换的数据预处理算法,测试表明效果较优。分析了电火花加工工艺的特点及其复杂性,提出了基于神经网络的电火花加工工艺选择模型,该模型能模拟熟练操作者的决策过程。测试结果表明,该模型能真实反映机床本身的工艺特点,模型值和实测值相差较小,能实现在给定加工要求下电加工参数的自动选择。     

考虑动态特性的快刀虚拟加工与参数优化选择

快速伺服刀架固有的动态特性是影响面形精度的主要因素,为了定量研究伺服刀架动态性能对面形精度的影响,分析了快速伺服车削特性,提出以系统的观点来进行虚拟加工并给出了快刀虚拟加工流程和参数优化选择流程,伺服刀架的闭环动态辨识模型对于数据模型的响应即为虚拟加工面形。介绍了基于MATLAB的数据模型生成及动态辨识模型获取方法,在此基础上,进行了实例仿真。仿真结果表明:伺服刀架的动态特性使得加工面形存在一定幅值衰减和相位滞后,不同加工参数下的幅值衰减和相位滞后差别较大。定量分析结果有助于加工参数的优化选择,为下一步研究超精密快速车削的工艺优化,以及精密高效加工提供指导和依据。     

基于正交试验和BP神经网络的Ti-6Al-4V合金电火花线切割工艺参数优化

针对切削性能差难以加工的Ti-6Al-4V合金进行了电火花线切割加工试验研究,运用正交试验的方法对工艺数据进行极差、方差分析,探究电火花线切割加工的规律和特性。重点分析脉冲宽度、脉冲间隔、功放管数和运丝速度等工艺参数对钛合金加工质量的影响,取得了线切割最优化参数组合。搭建了基于L-M优化算法的BP神经网络的线切割加工工艺网络预测模型,该模型训练速度快、预测精度高,可为Ti-6Al-4V合金的切割提供可靠的加工质量预测,对实际加工的参数选择具有一定的参考作用。     

BDK-I电火花加工监视器

电火花加工是在液体介质中工具电极与工件间极小的间隙中进行的。直接观测和判别电火花加工的放电状态非常困难。加工过程中,放电间隙经常变化,其状态瞬息万变,各种放电加工状态(如空载,火花,电弧,短路,搭桥等)总是交错出现的。由于伺服进给速度的不同和脉冲参数选择的变化,使这几种状态在整个加工过程中所占的比例不同。而保持加工的稳定性,提高正常放电状态的比例,对提高加工工艺指     

Fabricating micromilling tool using wire electrodischarge grinding and focused ion beam sputtering

In the present research, wire electrical discharge machining (WEDM) of γ titanium aluminide is studied. Selection of optimum machining parameter combinations for obtaining higher cutting efficiency and accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complicated stochastic process mechanisms. In general, no perfect combination exists that can simultaneously result in both the best cutting speed and the best surface finish quality. This paper presents an attempt to develop an appropriate machining strategy for a maximum process criteria yield. A feed-forward back-propagation neural network is developed to model the machining process. The three most important parameters – cutting speed, surface roughness and wire offset – have been considered as measures of the process performance. The model is capable of predicting the response parameters as a function of six different control parameters, i.e. pulse on time, pulse off time, peak current, wire tension, dielectric flow rate and servo reference voltage. Experimental results demonstrate that the machining model is suitable and the optimisation strategy satisfies practical requirements.     

ELECTRIC DISCHARGE MILLING AND MECHANICAL GRINDING COMPOUND MACHINING OF SILICON CARBIDE CERAMIC

Silicon carbide (SiC) ceramics have been widely used in modern industry. However, the manufacture of SiC ceramics is not an efficient process. This paper proposes a new technology of machining SiC ceramics with electrical discharge milling and mechanical grinding compound method. The compound process employs the pulse generator used in electrical discharge machining, and uses a water-based emulsion as the machining fluid. It is able to effectively machine a large surface area on SiC ceramics with a good surface quality. In this paper, the effects of pulse duration, pulse interval, peak voltage, peak current and feed rate of the workpiece on the process performance parameters, such as material removal rate, relative electrode wear ratio and surface roughness, have been investigated. A L₂₅ orthogonal array based on Taguchi method is adopted, and the experimental data are statistically evaluated by analysis of variance and stepwise regression. The significant machining parameters, the optimal combination levels of machining parameters, and the mathematical models associated with the process performance are obtained. In addition, the workpiece surface microstructure is examined with a scanning electron microscope and an energy dispersive spectrometer.     

基于人工神经网络的电火花加工工艺建模方法研究

电火花加工是一个受多参数影响的复杂随机过程,很难建立一个适当的机理模型。用神经网络技术以铜加工SKD-Ⅱ为例建立了电火花加工工艺模型,并依据工艺样本中各参数数据的不同特点采用了不同的预处理方法,测试表明效果较好,所建模型能精确地预测出给定条件下的加工工艺参数,反映了该机床的加工工艺规律。另外,采用石墨加工SKD-Ⅱ工艺数据验证了该方法的通用性及有效性。     

Super-high-thickness high-speed wire electrical discharge machining

High-speed wire electrical discharge machining (WEDM-HS) of materials of super-high thickness (more than 1000 mm) is a challenging problem. First, sufficient energy is required to maintain the inter-electrode normal discharge. Next, there must be adequate inter-electrode dielectric fluid. Third, in order to generate a smooth cut surface, it is necessary to suppress the vibration of the wire electrode to reduce vibration lines on the cutting surface. To better understand these challenges, the energy and the flow of the medium between two electrodes were analyzed, allowing the establishment of a relevant model. The results indicated that for super-high-thickness machining, the pulse energy must be adequate to compensate for the energy consumed in the molybdenum wire and inter-electrode working liquid. In addition, the running speed of the wire electrode should be improved to ensure that there is a sufficiently high flow rate of the dielectric fluid. The servo control mode of the existing machine tools and dielectric fluid were improved and then a process experiment was performed. The experimental results show that the process can be carried out efficiently and stably and the workpiece surface can be cut smoothly using the improved working liquid and servo control mode.     

电火花线切割加工中线电极的动态特性仿真与实验研究

研究慢走丝电火花线切割加工中电极振动对加工状态的过程的影响。应用计算机仿真技术,分析连续放电力作用下线的振动模态以及对放电点转移和分布的作用。结果表明,加工工艺参数明显影响放电点的转移与分布,适当地选择工艺参数可获得最佳的放电分布率。该研究对提高慢走丝加工稳定性,防止断丝的发生提供了相应理论依据。     

Electrical discharge precision machining parameters optimization investigation on S-03 special stainless steel

S-03 is a novel special stainless steel, which is widely used in precision aerospace parts and electrical discharge machining technology has the merit of high-accuracy machining. This paper aims to combine gray relational analysis and orthogonal experimental to optimize electrical discharge high-accuracy machining parameters. The four process parameters of gap voltage, peak discharge current, pulse width, and pulse interval are required to optimize in the fewest experiment times. The material removal rate and surface roughness are the objective parameters. The experiment were carried out based on Taguchi L9 orthogonal array, then we carried out the gray relational analysis to optimize the multi-objective machining parameter, finally, we verified the results through a confirmation experiment. The sequence of machining parameters from primary to secondary are as follows: discharge current 7A, pulse interval 100 μs, pulse width 50 μs, and gap voltage 70 V. Using the above machining parameters, we can obtain good surface roughness Ra1.7 μm, and material removal rate 13.3 mm³/min. The machined work piece almost has no surface modification layer. The results show that combining orthogonal experiment and gray relational analysis can further optimize machining parameters, the material removal rate increased by 23.8 %, and the surface roughness almost has no change.     

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).     

Influence of machining parameters on surface roughness in finish cut of WEDM

Surface roughness is significant to the finish cut of wire electrical discharge machining (WEDM). This paper describes the influence of the machining parameters (including pulse duration, discharge current, sustained pulse time, pulse interval time, polarity effect, material and dielectric) on surface roughness in the finish cut of WEDM. Experiments proved that the surface roughness can be improved by decreasing both pulse duration and discharge current. When the pulse energy per discharge is constant, short pulses and long pulses will result in the same surface roughness but dissimilar surface morphology and different material removal rates. The removal rate when a short pulse duration is used is much higher than when the pulse duration is long. Moreover, from the single discharge experiments, we found that a long pulse duration combined with a low peak value could not produce craters on the workpiece surface any more when the pulse energy was reduced to a certain value. However, the condition of short pulse duration with high peak value still could produce clear craters on the workpiece surface. This indicates that a short pulse duration combined with a high peak value can generate better surface roughness, which cannot be achieved with long pulses. In the study, it was also found that reversed polarity machining with the appropriate pulse energy can improve the machined surface roughness somewhat better compared with normal polarity in finish machining, but some copper from the wire electrode is accreted on the machined surface.