Measurement method for volumetric error of five-axis machine tool considering measurement point distribution and adaptive identification process

Abstract

To improve the machine tool accuracy, geometric error identification is required for volumetric error compensation. This paper presents a method for the geometric error identification of a five-axis machine tool that considers the optimised distribution of measurement points and accurate description of geometric errors. The measurement is performed using a laser tracker that permits rapid error data collection over a large measurement range. In the volumetric error modelling, the geometric errors are described as position-dependent Chebyshev polynomials. Hence, the identification of geometric errors is converted into the identification of polynomial coefficients. In the identification process, a distribution method for measurement points is proposed to improve the identification accuracy by minimising the influence of measurement error on the identification result. At the same time, an adaptive approach is introduced to accurately define the polynomial orders of geometric errors to improve the identification accuracy. Simulations and experiments are conducted to verify the geometric error identification method. In addition, the proposed method is compared with other methods. Based on the identification result of geometric errors and the volumetric error model, the volumetric error of any position in a workspace can be predicted and further compensated.