Modelization and Identification of Feed Drive Axis in CNC Machine Tools Using Two-Mass Model and Particle Swarm Optimization

The feed drive axis of a computer numerical control (CNC) machine tool is a composite mass system. This study modelized the feed drive axis of a machine tool into a two-mass model, and then used particle swarm optimization (PSO) to identify the physical parameters of the feed drive axis two-mass model for subsequent application. The modelization and identification method for the machine tool feed drive axis developed in this study could identify the following parameters: equivalent inertia of the driving motor and ball screw of the feed drive axis; equivalent mass of the moving table and nut; equivalent viscous damping among motor, ball screw, and nut; equivalent viscous damping between the moving table and linear guides; equivalent axial stiffness; and internal damping coefficient. The frequency characteristics of the feed drive axis were used as constraints of PSO to improve the identification results. The experimental results of the CNC lathe machine tool demonstrated the feasibility of the developed approaches.