Dynamic error modeling of CMM based on Bayesian statistical principle

Abstract

The dynamic error sources of CMM were analyzed and the character of the dynamic error data was investigated in this paper. Based on the character, the dynamic error model of CMM was built by using Bayesian statistical principle combined with the standard quantity interposition method. The specific error model building procedures was deduced. The CMM dynamic error separating and contrasting experimental devices were designed by using the laser interferometer and the measuring block group. The theoretical analysis and the experiment result indicate that all influences of the CMM dynamic error sources is considered in the model building method by using Bayesian statistical principle combined with the standard values interposition method which meets the CMM working condition. The error model accuracy reaches 2.4 μm and meets the CMM demand. The needed error data size is greatly reduced by using the dynamic error model building method. The error separating principle by lapping-in the measuring block group is simple, which is implemented easily and meets the timing dynamic error correcting needs of the ordinary CMM user.