共查询到20条相似文献,搜索用时 140 毫秒
1.
2008年全国电火花成形加工技术研讨会于2008年10月10~12日在北京市科学技术研究院报告厅举行。此次会议由中国机械工程学会特种加工分会电火花成形加工技术委员会主办,北京市电加工研究所承办。中国机械工程学会特种加工分会副理事长、电火花成形加工技术委员会主任曹凤国,电火花成形加工技术委员会副主任杨大勇、山昌祝、郭永丰共同主持了会议。 相似文献
2.
3.
4.
5.
6.
7.
8.
9.
10.
传统加工硬质合金刀具多采用磨削方式.采用磨削成形后再电火花精加工方式获得硬质合金刀具,能很好地解决很多纯粹用磨削加工方法遗留下的缺陷.另外,在初步电火花加工成形后采用电火花涂覆,可有效解决涂层与基体间附着力差的问题. 相似文献
11.
提出了压电陶瓷(piezoelectric ceramic transducer,PZT)激励同步压缩放电通道微细电火花加工,目的在于改善微细电火花加工的放电环境。介绍了PZT激励同步压缩放电通道微细电火花加工原理,研究了开路电压、脉冲宽度、脉冲频率和峰值电流对其电极损耗和材料去除率的影响,并与不采用压缩通道方法的微细电火花加工进行了对比。结果表明:同等条件下,采用PZT激励同步压缩放电通道技术,提高了加工过程的稳定性和材料去除率,降低了电极损耗率,有效改善了放电环境。 相似文献
12.
介绍了电解加工的基本原理及其加工工艺优点 ,阐述了ECM(电化学溶解及电火花熔蚀)/EDM(电火花放电腐蚀成型)复合加工过程 ,以及国外深小孔ECM/EDM复合加工的发展现状 相似文献
13.
超声电火花复合加工在模具制造中的应用 总被引:4,自引:1,他引:3
电火花加工技术能对高硬度、高强度金属材料加工,但存在加工效率低和加工表面质量不好的缺陷。通过对超声电火花复合加工研究,探讨了放电参数对加工速度影响的规律,指出超声电火花复合加工工艺可弥补电火花加工在加工效率及质量方面的不足,将会对模具型腔、型芯的制造产生重要影响。 相似文献
14.
15.
由于钛合金的超高硬度,使得切削加工十分困难,且成本巨大,即使耗费很大代价加工出来的产品,其加工质量往往不尽人意。因而,在研究国内外电火花加工技术最新成果的基础上,设计钛合金电火花加工试验,将加工速度、三维表面粗糙度作为评价加工性能的指标,分析了占空比、峰值电流、电压对钛合金加工的影响规律之后,深入研究了钛合金电火花成形加工的工艺特性;以MATLAB R2007b软件为平台,利用BP神经网络建立钛合金电火花加工工艺参数优化模型,并通过加工实验,对其预测结果进行评价。 相似文献
16.
Shuyang Liu Yumei Huang Yan Li 《International Journal of Machine Tools and Manufacture》2011,51(7-8):653-659
The electrical discharge machining (EDM) process is, by far, the most popular amongst the non-conventional machining processes. The technology is optimum for accurate machining of complicated shapes in hard materials, required in the modern industry. However, although a lot of EDM machines are widely applied for many years, fundamental knowledge of the process is still limited. The complex nature of the process involves simultaneous interaction of thermal, plasma temperature and electromagnetism factors, which makes the machining process modeling very difficult. In this paper, based on the analysis of the electric discharge machining (EDM) process, a plate capacitor model is constructed to describe the discharging process in a pulse time. The whole EDM process is divided into four stages, successively as interelectrode electric-field establishment, electric discharge channel formation, stable EDM and deionization, the interaction of each stage and the distribution function of EDM energy are deduced using the field electron emission theory. For the purpose of analyzing the effect of the single factor, a set of machining through-hole experiments were carried out and investigated. The study shows that critical electric-field intensity and the effective discharging time rate play major roles on the improvement of machining efficiency; the model can explain the differences of machining efficiency using different materials of tool pole and different EDM parameters; and the theoretical results are concordant with the experimental data well. 相似文献
17.
B. Izquierdo J.A. Sánchez S. Plaza I. Pombo N. Ortega 《International Journal of Machine Tools and Manufacture》2009,49(3-4):220-229
The electrical discharge machining (EDM) process is, by far, the most popular amongst the non-conventional machining processes. The technology is optimum for accurate machining of complex geometries in hard materials, as those required in the tooling industry. However, although a large number of EDM machines are sold every year, scientific knowledge of the process is still limited. The complex nature of the process involves simultaneous interaction of thermal, mechanical, chemical and electrical phenomena, which makes process modelling very difficult. In this paper a new contribution to the simulation and modelling of the EDM process is presented. Temperature fields within the workpiece generated by the superposition of multiple discharges, as it happens during an actual EDM operation, are numerically calculated using a finite difference schema. The characteristics of the discharge for a given operation, namely energy transferred onto the workpiece, diameter of the discharge channel and material removal efficiency can be estimated using inverse identification from the results of the numerical model. The model has been validated through industrial EDM tests, showing that it can efficiently predict material removal rate and surface roughness with errors below 6%. 相似文献
18.
19.