Parameters Optimizing Research of WEDM Engineering Ceramics Material Based on GA-neural Networks

The main electrical parameters,including impulse current,impulse width,work voltage,impulse separation,the count of power tube,and homologous outputing parameters were studied,trained and optimized by applying GA-high steps faintness BP neural networks during the WEDM processing,it is showed that the neural networks have the ability of prediction.Using optimizing(electrical) parameters to do experiments research of WEDM engineering ceramics Al_2O_3-TiC(content 30%),the obtained result is accordant with the result of GA-neural networks.The least surface remnant stress and optimum wearable intension in the processing surfaces of the Al_2O_3-TiC were obtained