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The precision of high-speed CNC (Computer Numerical Control) machine are greatly influenced by the dy- namic characteristics of servo system. To establish the servo system model accurately, the internal signals of NC, e.g. mo- tor current and rotate speed were adopt as the input or output signal for the system. The ARMA linear identification model was also established to identify the dynamic parameters of the mechanical parts in the servo system, including equivalent inertia, equivalent damping and so on. The friction Stribeck curve was obtained by necessary experiments. The nonlinear friction model was linearized by using higher-order Taylor expansion, and the five parameters of the Stribeck friction model were identified. To verify the effectiveness of the closed-loop identification, experiments are carried out on the feeding system of a commercial NC machine. Signals of servo motor current and rotating rate which are offered in many modern CNC machine tools are needed for the identification and experiments results show that the proposed method per- forms well with rapid convergence and accurate results and parameters of Stribeck model can be obtained accurately by identification. The method is suited for industrial condition and has its practicality.

Dynamic Parameters Identification for the Feeding System of Commercial Numerical Control Machine