Thermal error modelling of gear measuring instrument based on principal component regression

Abstract

As gear measuring instruments (GMI) are frequently used at the production site, the influence of temperature on their accuracy and stability becomes non-negligible. The existing standards and technologies only consider the error modelling and compensation problem when the GMI is in a uniform temperature field and is not suitable for the production site environment with a large temperature change rate and large temperature gradient. The paper delves into the problems of GMI thermal error modelling at the production site. First, the temperatures of the GMI and its surroundings were measured using multiple temperature sensors. The parallelism thermal errors between centres and the Z-axis (referred to as parallelism thermal errors) and the y-direction spatial thermal errors (referred to as spatial thermal errors) were also measured by the probe and laser interferometer synchronously. Then, the models of them were established based on principle component regression (PCR). As evidenced by the experimental results, the fitting determination coefficient of the models are both greater than 97%, and the prediction determination coefficient is greater than 90%, demonstrating that the models are precise and robust.