Adaptive grinding method and experimental verification of worm gear tooth surface knife marks

Abstract

Aiming at the problem that the basic impedance control has great impact force and is difficult to cope with environmental changes when it contacts with the tooth surface of worm gear, an adaptive impedance control method based on genetic algorithm was proposed. The influence law of spindle speed, feed speed and grinding force on the surface quality of worm gear tooth surface is analyzed. With material removal rate as the optimization objective, an optimization model of grinding process parameters is established based on particle swarm optimization algorithm, and the optimal grinding process parameters for industrial robot grinding worm gear tooth surface knife marks are obtained: Spindle speed (n=3087.82r/min), Feed speed (vf=0.51mm/s), Normal grinding force (F=19.9N). The experimental results show that the roughness of worm gear tooth surface is increased from 0.941 to 0.719 by using the optimized grinding process parameters. Moreover, this method can effectively suppress the external force influence of industrial robots in the process from free space to constrained space, and the force fluctuation is significantly reduced after contact stabilization, and it has stronger environmental adaptability and force control performance.