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1、国内图书分类号：TG0661国际图书分类号：621.9.048工学硕士学位论文电火花分层铣削加工电极损耗预测技术的研究硕 士 研 究 生： 郑春花导师： 白基成教授申请学位级别： 工学硕士学 科 、 专 业： 机械制造及其自动化所 在 单 位： 机电工程学院答 辩 日 期： 2007 年 7 月授予学位单位： 哈尔滨工业大学Classified Index: TG0661U.D.C.: 621.9.048A Dissertation for the Degree of M. Eng.STUDY ON ELECTRODE WEARPREDICTION TECHNOLOGY OF EDLAYERE
2、D MILLINGCandidate：Supervisor：Academic Degree Applied for：Zheng ChunhuaProf. Bai JichengMaster of EngineeringSpecialty：MechanicalManufacturingand AutomationAffiliation：Date of Defence：Degree-Conferring-Institution：School of Mechanical Electrical EngineeringJuly, 2007Harbin Institute of Technologyand
3、哈尔滨工业大学工学硕士学位论文摘要随 着 数 控 电 火 花 加 工 技 术 的 发 展 ， 有 关 电 火 花 分 层 铣 削 加 工 (ED LAYERED MILLING)技术的研究逐步活跃起来，并日益引起国内外电加工 界的高度重视。与传统电火花成形加工相比，电火花分层铣削加工的优势是 明显的。它具有不需要制作专用成形电极、缩短产品生产周期、减少加工费 用、提高加工的灵活性等一系列特点。但由于电火花铣削加工也是放电加 工，工具电极同样存在损耗的问题，这样就影响了加工精度。准确预测以及 补偿电极损耗是提高加工精度的有力手段。 本文基于电极等损耗加工的原理采用正交实验法对电火花分层铣削加工
4、的电极损耗进行了实验研究。研究了峰值电流、脉冲宽度、脉冲间隔、冲油 压力、电极截面积、铣削深度等因素在电火花分层铣削加工中对电极损耗的 显著性。讨论了电火花分层铣削加工电极损耗的规律，提出了合理配置各加 工参数的优化方案。研究了各个因素影响工具电极损耗的情况，分析了其原 因。 由于电火花铣削加工电极损耗规律复杂，影响因素很多，加工间隙状态 随时在发生变化，很难建立它的电极损耗数学模型。本文针对电火花铣削加工时变非线性的特点，采用径向基函数（简称 RBF）网络构筑了电火花铣 削加工电极损耗预测模型。用实验数据对此网络进行训练，使之预测出一定 条件下的电极相对损耗，从而可在加工中实时计算出损耗量，
5、为实现电极损耗的在线动态补偿打下了基础。利用所构筑的 RBF 网络预测模型进行了电极损耗预测实验，与 BP 网络的预测效果进行了比较，发现 RBF 网络的预 测效果明显优于 BP 网络的预测效果。RBF 网络的预测误差小于 8%。关键词电火花分层铣削加工；等损耗；电极损耗预测；RBF 神经网络-I-哈尔滨工业大学工学硕士学位论文AbstractWith the development of CNC EDM technology, the research of ED LAYERED MILLING gradually becomes an active subject and it is pa
6、id more attentions in the field of EDM at home and abroad. Compared to traditional EDM, ED LAYERED MILLING has some obvious advantages of saving a large number of shaped electrodes, shortening production cycle, reducing processing costs, increasing the flexibility of processing and so on. Because ED
7、 MILLING belongs to EDM, it also has the problem of electrode wear which can affect the final machining accuracy. Accurate prediction and the compensation of electrode wear is a efficient method of increasing the processing accuracy. Based on the principle of equivalent wear and orthogonal experimen
8、t, a lot of experiments have been done to measure peak current, pulse duration, pulse separation, oil pressure, electrode cross section and the machining depth. The distribution effects of these parameters were analyzed to research the rules of the electrode wear of ED LAYERED MILLING. An optimizati
9、on program of distribution of the processing parameters has been proposed. The impactions of various factors on electrode wear have been study and the reasons of them have been analyzed in the paper. Because ED MILLING has complex rules, many factors impact the electrodewear and the gap state always
10、 changes in the processing. It is difficult to establish a mathematical model of electrode wear. According to the nonlinear characteristics with time varying of ED MILLING, an electrode wear prediction model using RBF network was established in this paper. The network was trained using experimental
11、data and to predict the electrode wear under certain conditions, which make it is possible to calculate the wear volume in a real-time processing and lay the foundation of dynamic compensation of the electrode wear on-line. Compared with the BP network, the result of electrode wear prediction of RBF
12、 network is better. The prediction error of RBF network was less than 8%.KeywordsED LAYERED MILLING; Equivalent wear; Prediction of electrode wear; RBF neural network- II -哈尔滨工业大学工学硕士学位论文目录摘要 .I Abstract . II第 1 章 绪论 . 1 1.1 课题的来源和研究目的及意义 . 1 1.2 国内外电火花铣削加工及其电极损耗对策的研究现状 . 2 1.3 论文的主要工作和研究内容 . 6 第 2 章 电火花铣削加工中电极损耗补偿策略 . 7 2.1 电极损耗补偿策略 . 7 2.1.1 减小电极损耗 . 7 2.1.2 电极的更换和修整 . 8 2.1.3 电极损耗的在线补偿 . 10 2.2 电极等损耗加工工艺的实现 . 11 2.3 本章小结 . 13 第 3 章 正交实验设计及其结果分析 . 15 3.1 实验装置 .
