The Study On CNC Grinding Parameters Optimization And BP Network Model Of Engineering Ceramics

Process parameters are the important factor to machining effect and the important symbol to the development level of engineering ceramics CNC grinding in the CNC grinding for engineering ceramics. So parameters optimization and model are studied experimentally in this paper.The factor and degree are studied to affect the machining time, grinding head wear and breakage of the CNC grinding for engineering ceramics through experiment in the paper. First of all, select the affecting factors that are the spindle speed, feed speed, feed rate and grinding head particle, and select the process effects that are the machining time, grinding head wear and breakage to design the orthogonal experiment and build the orthogonal array. The second, according to the results of orthogonal experiment, the signal-to-noise ratio is used to analyze the affecting regularity of the process parameters to the process effects. The third, according to the analysis of signal-to-noise ratio, the grey relational grade is used to get parameters optimization under the multi targets on CNC grinding. the test result indicates that the method can improve the machining time, grinding head wear and breakage based on signal-to-noise ratio and grey relation grade.The last but not the least, the orthogonal result of the CNC grinding process parameters for the engineering ceramics is used to be learning sample in the BP neural network to build multi targets prediction model for the CNC grinding. And simulate the prediction model with any parameters and the multi parameters optimization to prove the prediction effect and the best parameters optimization, and they are confirmed.