Rotation error separation of a UTF300 high-speed and precision motorized spindle

Abstract

To improve the measurement accuracy of high-speed and precision motorized spindle rotary error as the research objective, based on the three-point method, an error separation model and an objective optimization function for noise-containing signals are developed. To improve the convergence speed, globally optimize the model objectives, and obtain the best optimization region of the sensor mounting angle, it is proposed that an enhanced adaptive particle swarm optimization algorithm be used. With the improved particle swarm algorithm, the convergence speed was greater than that of the primary particle swarm algorithm by more than 50%. The spindle radial rotation error was experimentally measured and separated using a high-speed vertical machining center, and the deviation between the separation result and the experimental rotation error was 4.5%, indicating that the separation result's accuracy was high. It also proved the correctness and feasibility of the optimization algorithm.