Adaptive compensation of the transmission errors in rack-and-pinion drives

Abstract

Rack-and-pinion drive systems are commonly used in large machine tools. When considering the achievable path accuracy, the transmission errors of the gearing are of significant importance. Assembly and manufacturing tolerances coupled with load-dependent deformation of the gearing components lead to periodic position deviations, which cannot be satisfactorily suppressed by the position control.This paper describes a novel approach to minimize the individual errors of a drive by adaptive compensation in the control utilizing machine learning algorithms. Since both kinematic deviations and load-dependent deformations are considered, the path accuracy can be increased for a wide range of operating conditions.