电火花微孔加工工艺规律的研究

【作者】 周明；

【导师】 贾振元；

【作者基本信息】 大连理工大学 ， 机械电子工程， 2002， 硕士

【摘要】 微孔加工是电火花微细加工的重要组成部分，电火花微孔加工技术随着微机械、精密机械、光学仪器等领域的不断拓展而得到广泛的关注。电火花微孔加工以其加工中受力小、加工的孔径和深度由调节电参数就可得到控制等优势，使其在各国的研究日益活跃。 本文从电火花的加工机理出发，以电火花微孔加工作为研究对象，通过实验研究在微孔加工环境下，各电参数对工艺指标的影响规律。选用常用的碳钢和铝合金作为实验用工件材料，工具电极选用铜电极，分别实验单项参数对工艺指标的影响规律，最后得出各主要放电参数如脉冲放电时间、脉冲间隔时间、间隙电压和峰值电流等的选择原则与规律。在此基础上，利用正交实验法设计并进行实验，得出各电参数对各项工艺指标的影响次序与大小，分清主次，从而做到可根据不同工艺指标的要求，调节各电参数以达到高效稳定的加工。 在实验的基础上，通过应用人工神经网络的B-P算法，建立电火花加工工艺模型，利用实验结果作为神经网络学习的样本，对电火花加工工艺模型在MATLAB软件上进行训练，用训练好的模型对工艺规律进行仿真，利用仿真结果进一步体现电火花微孔加工的工艺规律，实现工艺参数的优化选择。更多还原

【Abstract】 The Electronical Discharge Micro-hole Machining (EDMM) has taken an important part in Electronical Discharge Superfine Machining. Its technology has attracted great notice in many countries brought on by the continuous technical development in such fields as micro-mechanism field, superfine mechanism field and optical instrument field, etc. and its research and development have also been gradually in full swing due to the advantages EDMM showed over those of other traditional machining methods, for example, little or no power exerted on the machined parts when machining, easily controlled diameters and depths by the convenient adjustment of the erosion parameters, etc..In this paper, EDMM has been set as the main object of this research work carried out by experiments under the micro-hole machining situations, testifying the theory and results of Electronical Discharge Machining (EDM) mechanism applied in these situations, helping to deduce the relationship between the specified technical goal and any main erosion parameter. Commonly used steel and aluminum alloy were selected as the work pieces, copper was used as tool material. The experiments were carried out to investigate how the single erosion parameter affects the machining process. In the end, generalize the principle and rules of selecting these main erosion parameters such as pulse duration time, pulse off time, gap voltage and discharge current, etc.. The further experiments devised by crossing experiment method showed the affecting sequence of these parameters to different technical goal. The results of these experiments indicate how to achieve the stable and efficient machining performance by the adjustment of these erosion parameters to the requirement of different technical goal.Based upon the experiments mentioned above, the results of which were selected as learning samples, EDMM model was created by the application of the B-P Arithmetic of Artificial Neural Network into this model. It was trained and then simulated on the platform of MATLAB. The results of simulation further reflect the EDMM technical rules and help to obtain the optimized combination of technical parameters.更多还原