摘要：High speed cutting process is a very complicated process; cutting parameters have a significant effect on cutting process and play a key role in the process of product manufacturing. The overall scheme of high speed cutting parameter optimization and its fault diagnosis have been introduced. The mathematical model of the selected cutting parameters was established and the optimized parameters were obtained by combining the experimental design with the technology of data processing. The statistical description of high speed cutting process control was introduced and the fault diagnosis model of cutting parameter optimization by using the neural network was proposed. Finally, the mathematical model in the present study is validated with a numerical example. The results show that the present method solved the problem of poor universality of high speed cutting data effectively and avoided the inaccuracy of physical and chemical mechanism research. Meanwhile, the present study prevents the passive checks of the cutting and gets better diagnosis of the complicated cutting fault type.
