A geometric prediction model of surface morphology in micro-EDM considering stochastic characteristics of discharge crater size

Accurate prediction of surface morphology is closely related to the application range of micro-EDM. Most of the existing prediction models do not consider the stochastic characteristics and uncertainty of the discharge crater, which can produce great differences with the experimental results. Aiming at these problems, the stochastic characteristic of the discharge crater size was studied, and a simulation model was established to predict the surface topography of EDM considering the stochastic characteristics of crater size. Firstly, the stochastic characteristics of the crater size were investigated through the finite-successive pulses discharge method and characterized from the perspective of probability theory. The stochastic characteristics were explained by analyzing discharge waveforms. Secondly, the response surface method (RSM) was used to map the corresponding relationship between the input machining parameters and the distribution characteristics of crater size. It was observed that the RSM model can accurately predict the distribution characteristics of crater size in the range of parameters selected in this study. Finally, models based on stochastic distribution of crater size (MSDS) and fixed crater size (MFS) were established respectively. By analyzing the characteristics of the simulated surfaces and the machined surface, it was found that the surface features of MSDS are closer to the real surface features. Compared with MFS, the roughness prediction error and the average of overall error of MSDS are reduced by 1.01% and 18.97%, respectively. The results of this work are helpful to understand the randomness and realize the controllability of EDM.