Research Of EDM Electric Parameters Optimization Based On Multi Objective Genetic Algorithm

With the development of precision and miniaturization, micro-hole processing has attracted people’s attention. As one of the important ways of micro-hole machining, microhole EDM technology has attracted more and more attention from the academic and industrial fields because of its non-contact machining and special hardness metals, therefore it is widely used in mechanical, aerospace, electronics, equipment, mold manufacturing, and many other fields. But because the characteristics of the small micro discharge area, small single discharge pulse energy and small electric pit, resulting in processing disadvantages of poor quality, low processing efficiency, and electrode loss difficult to precisely control and other shortcomings, which seriously restrict the application and development of it. Thus, how to optimize machining parameters and improve the surface quality and machining speed, reduce the loss rate of micro-hole have become a concern.The effects of micro-hole machining parameters on the surface quality, processing speed and electrode wear rate are discussed in this paper. It is indicated that the Pulse power parameters such as pulse width, pulse interval and peak current directly influence the process parameters. By optimizing the parameters of the pulse power supply, it can ensure the surface roughness get faster processing speed and less electrode wear. Based on improving the processing index, the NSGA-II algorithm with fuzzy interval programming is used to optimize the machining parameters in this paper. First of al, according to the existing electric spark discharge data, the parameter model of electric spark discharge is established by using the neural network algorithm, and validated by the test of model accuracy. Secondly, the NSGA-II algorithm with fuzzy interval programming is used to optimize the parameters of EDM. At the same time, in order to prove the superiority of the algorithm, this paper uses two kinds of algorithm to carry on the simulation contrast test, to carry on the further verification to this algorithm.In this paper, I write the related algorithm, and compare with the conventional fuzzy control optimization algorithm. The result shows that the NSGA-II algorithm with fuzzy interval programming used to optimize the machining parameters, which not only can obtain excel ent surface machining quality, but also can get a better processing speed and electrode wear rate. This study provides a theoretical and practical basis for the future research of EDM pulse parameter settings.