Calibration and compensation of machine tool volumetric error using a laser tracker

Machine tools are widely used in industrial manufacturing. Volume positioning error calibration and compensation are important for ensuring manufacturing accuracy. However, there are two challenges associated with traditional methods. First, the machine tool coordinate system and measurement system must be registered before measuring, but the existing registration methods cannot manage the anisotropic situation, leading to low registration accuracy. To solve this problem, a closed-form iteration combined weighting method is developed. Second, the verification of volumetric error in the entire workspace usually requires hundreds of measurements, which makes the measurement process very complex and time-consuming and possibly affects the calibration accuracy. To this end, a Gaussian process regression (GPR)-based volumetric error prediction and compensation method is improved to simplify the measurement process and ensure accurate calibration and compensation. Simulations and experiments show that the proposed closed-form iteration combined weighting method can improve the registration accuracy, and the proposed GPR-based volumetric error prediction and compensation method can achieve high accuracy with a simple measurement process. Therefore, the proposed methods provide an effective path for machine tool volume positioning error calibration and compensation.