Optimization of Servo Parameters for Enhanced Dynamic Behavior of Direct Feed System with Hybrid FEM and PLS Regression

Abstract

Optimal servo dynamics of a direct feed system driven by linear motor play an important role in improvement of its dynamic behavior and the precision of its processing products. An optimization method for enhancement of the dynamics of the drive system is proposed with hybrid FEM and PLS regression. Dynamic stiffness spectrogram of the servo system, also as optimization performance evaluation, is applied to obtain its resonance frequency. A force pulse excitation-based dynamic stiffness measurement scheme is introduced to acquire the spectrum diagram. For simulation of the stiffness characteristic, a FE model of the drive mechanism is developed with dynamic conjunctions, which parameters are considered to be related to the servo parameters. A relationship model between the stiffness variables of the conjunctions and the servo parameters is established with PLS regression. Based on the regression equation, the optimization model is constructed for the dynamics enhancement. To validate the feasibility of the scheme, an experiment was conducted on a domestic test rig. The results show that the method can effectively extend non-resonant frequency and improve the dynamics with 10.4 Hz higher in first-order modal frequency and 6.7 Hz higher in second-order than the corresponding results of the samples in the mean value from random tests.