Research On Optimization Of Electrical Parameters Of EDM Machining7075Aluminum Alloy

7075aluminum alloy has many advantages comparing with conventional materials toolsteel, such as, high strength, good thermal conductivity, corrosion resistance and good electricalperformance. So, its proportion of applications in plastic mold is growing in recent years. Sincethe structure of the plastic mold is usually more complex, traditional machining methods cannot meet their processing requirements, but the EDM technology has the ability to processcomplex shapes. The7075aluminum alloy EDM process is affected by many processparameters (especially electrical parameters), and the processing effect is difficult to control.Workpieces can only rely on the operator experience to process, so it is difficult to achieve theautomate production. Therefore, researching on the optimization of7075aluminum alloy EDMelectrical parameters has great significance for achieving the effect of process control and theautomation of processing.Based on the above issues, the Su-Field analysis method was used in the optimization of7075aluminum alloy EDM electrical parameters, the7075aluminum alloy EDM single pulsedischarge Su-Field model was establised, and the influence of electrical parameters onprocessing effects was obtained. Then, the paper studies the7075aluminum alloy EDM processexperiments. Using the experiment results as the sample data, the paper utilizes MATLABR2012a software to set up the7075aluminum alloy EDM effect prediction model which cancontrol EDM effects and optimize the selection of electrical parameters. Specific studies are asfollows:(1) The EDM principle, Su-Field analysis method, artificial neural networks and geneticalgorithms were analyzed. And, the7075aluminum alloy EDM electrical parameteroptimization general idea were determined.(2) The EDM Su-Field representation theory was studied. Based on the Su-Field analysismethod, the7075aluminum alloy EDM mechanism was analyzed. And the application of flowof Su-Field analysis method to solve the EDM discharge system problem was established. Lastthe Su-Field model of EDM single pulse discharge process was achieved. Based on the singlepulse discharge model, the influence of electrical parameters on processing effects wasanalyzed. Finally, for the EDM discharge instability, combined with76standard solutions, thesolutions were achieves.(3) The influence of electrical parameters for processing effects. Using copper as the toolelectrode,7075aluminum alloy as the processing object, EDM speed and surface roughness asthe index of single factor experiments, the paper obtains the relationship between the peak current, pulse width, pulse interval, open-circuit voltage and processing speed, surfaceroughness. The results of single factor experiments and the results of the analysis of the singlepulse discharge Su-Field model are consistency. The availbability of the single pulse dischargematerial-field model was proved.(4) Due to the interaction between the electrical parameters, the EDM7075aluminumalloy multi-factor experiments were studied by using the orthogonal experiment methods todesign experiments. Using the processing speed and surface roughness as process indicators,considered separately peak current, pulse width and pulse interval, each of five levels,25sets ofrepresentative experiments data are achieved.(5) Selecting22sets of experiments from the25sets of orthogonal experiments randomlyas study sample datas and the remaining3sets of datas as the test sample. The paper utilizes theBP neural network to set up the7075aluminum alloy EDM electrical parameter optimizationmodel. The results shows: the prediction accuracy of the model is well. For the given processindicators, combined with the genetic algorithm, the paper uses the7075aluminum alloy EDMprocess effects prediction model to optimize the electrical parameters. The results shows: the7075aluminum alloy EDM process effects prediction model can optimize the electricalparameters.