基于模糊PID短电弧铣削加工电极损耗研究与优化

发布时间：2018-04-23 23:35

本文选题：短电弧铣削加工 + 电极损耗　；参考：《新疆大学》2017年硕士论文

【摘要】：面对目前高硬度、高强度、高韧性难加工材料应用领域及范围的日益增多,特种加工以其独有的加工优势为机械制造业中遭遇的瓶颈开辟了一片新天地,其中包括短电弧加工,它主要是利用极间放电通道中产生的高温和爆炸力对工件进行去除加工,并且在加工中利用带一定压强的气液混合介质将熔化的金属废渣冲走。此过程中工具与工件之间本文首先分析了短电弧加工的放电机理,掌握放电通道形成原理、熟悉工件材料被蚀除过程,并采用Thermcamvision A40红外热成像仪观察了实际加工中极间温度的变化情况,为了避免发生短路时温度过高烧毁工件,对不同控制方法的优缺点进行比较后,本文提出在控制系统中引入模糊控制算法。本研究的出发点是对短电弧铣削加工进行优化,实现低电极损耗、高加工效率的目的。通过实验和阅读文献发现正常加工时,引起电极损耗的主要因素包括电参数(电压幅值、占空比、频率)的变化、电极材料的选取、工作介质的状态、进给量的大小。为了探究不同因素对电极损耗的影响情况,实验采用单因素分析法,在设定其他研究参数不变的情况下,选取多组试验参数进行对比,得出电极损耗相对较小的加工状态。但在实际加工中,由于放电参数不连续、蚀除材料未及时排除等原因会造成短路,此时工具电极与工件材料之间出现“机械加工”,这样会加剧电极的损耗量,降低工件质量。为了避免这种情况,本文提出建立基于模糊PID控制算法的自适应控制系统,将电信号的实际值与系统设定阈值的偏差及偏差变化率作为控制器的输入,根据控制系统制定的模糊规则自适应调整控制器的输出,并对此数学模型进行Simulink仿真验证其可行性。由于加工中通过电流大小来判断工件与工具的间隙,因此针对电流信号的采集,本文通过对比分析采用了PCI-1716数据采集卡,以Delphi 7.0作为开发工具,运用信号发生器SG2040A发送信号,将示波器所显示的波形与Delphi采集界面显示的波形进行对比,发现两组波形一致,验证了该采集系统的可行性。
[Abstract]:In the face of the increasing application field and scope of high hardness, high strength and high toughness materials, special machining has opened a new world for the bottleneck encountered in the mechanical manufacturing industry with its unique processing advantages, including short arc processing. It mainly uses the high temperature and explosive force produced in the inter-pole discharge channel to remove and process the workpiece, and the molten metal waste slag is washed away by the gas-liquid mixed medium with a certain pressure in the process. In this process, this paper first analyzes the discharge mechanism of short arc machining, grasps the principle of discharge channel formation, and is familiar with the etching process of workpiece material. Thermcamvision A40 infrared thermal imager is used to observe the change of interpolar temperature in actual processing. In order to avoid excessive temperature burnout of workpiece during short circuit, the advantages and disadvantages of different control methods are compared. In this paper, a fuzzy control algorithm is introduced into the control system. The purpose of this study is to optimize the short arc milling process to achieve low electrode loss and high machining efficiency. Through experiments and reading literature, it is found that the main factors causing electrode loss during normal processing include the change of electrical parameters (voltage amplitude, duty cycle, frequency), the selection of electrode material, the state of working medium, and the size of feed rate. In order to explore the influence of different factors on electrode loss, the single factor analysis method was used in the experiment. Under the condition of setting other research parameters unchanged, several groups of test parameters were selected for comparison, and the processing state of electrode loss was found to be relatively small. However, in practice, because of the discontinuous discharge parameters and the non-timely removal of the etched materials, the short circuit will occur. At this time, there will be a "machining" between the tool electrode and the workpiece material, which will aggravate the loss of the electrode and reduce the quality of the workpiece. In order to avoid this situation, an adaptive control system based on fuzzy PID control algorithm is proposed in this paper. The deviation between the actual value of electrical signal and the threshold value of the system and the rate of deviation change are taken as the input of the controller. The output of the controller is adaptively adjusted according to the fuzzy rules established by the control system, and the feasibility of this mathematical model is verified by Simulink simulation. Because the gap between the workpiece and the tool is judged by the current size in the machining process, the PCI-1716 data acquisition card is adopted in this paper by comparing and analyzing the current signal, and the signal generator SG2040A is used to send the signal with Delphi 7.0 as the development tool. By comparing the waveform displayed by oscilloscope with that displayed by Delphi acquisition interface, it is found that the two groups of waveforms are the same, which verifies the feasibility of the acquisition system.
【学位授予单位】：新疆大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TG661;TG54

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