Dynamic parameters' identification for the feeding system of computer numerical control machine tools stimulated by G-code

This study proposed a dynamic parameters’ identification method for the feeding system of computer numerical control machine tools based on internal sensor. A simplified control model and linear identification model of the feeding system were established, in which the input and output signals are from sensors embedded in computer numerical control machine tools, and the dynamic parameters of the feeding system, including the equivalent inertia, equivalent damping, worktable damping, and the overall stiffness of the mechanical system, were solved by the least square method. Using the high-order Taylor expansion, the nonlinear Stribeck friction model was linearized and the parameters of the Stribeck friction model were obtained by the same way. To verify the validity and effectiveness of the identification method, identification experiments, circular motion testing, and simulations were conducted. The results obtained were stable and suggested that inertia and damping identification experiments converged fast. Stiffness identification experiments showed some deviation from simulation due to the influences of geometric error and nonlinear of stiffness. However, the identification results were still of reference significance and the method is convenient, effective, and suited for industrial condition.