Spindle dynamics identification using particle swarm optimization

Optimal parameters to eliminate machining chatter may be identified using analytical stability models which require the dynamics of the tool-holder-spindle-machine assembly. Receptance coupling substructure analysis (RCSA) provides a useful analytical tool to couple measured spindle-machine dynamics with tool-holder models to predict the tool point frequency response function for the assembly. Previous research has demonstrated a procedure to determine all required spindle receptances from a single measurement, where each mode within the measurement bandwidth was modeled as a fixed-free Euler–Bernoulli beam and fit using a manual, iterative procedure. Here, a particle swarm optimization technique is described for fitting the spindle-machine measurement using a fixed-free Euler–Bernoulli beam model for each mode. The performance of the optimization process and RCSA in predicting the tool tip frequency response is evaluated and the results are presented.