Experimental Investigation of Dynamic Errors in Coordinate Measuring Machines for High Speed Measurement

Abstract

Accuracy enhancement of coordinate measuring machine (CMM) by software compensation for geometric and thermal error has proved its effectiveness in the modern manufacturing. In some applications, measurement errors can be reduced by more than 70% when using error compensation. However, due to the demand for shorter cycle times of measurement tasks, CMMs are increasingly required to be used at high measuring velocity. In such conditions, dynamic errors will certainly have a much more influence on the measurement accuracy and constitutes a barrier to the reduction of measuring cycle time. This paper presents an experimental investigation of dynamic errors in CMMs. A structured experimental design and improved statistical analysis tools are combined to evaluate the measurement parameters effects at high measuring velocity. Carried out on a bridge type CMM, these parameters are combined and used to investigate the variation of several dynamic error attributes. A laser interferometer system is used to assess error components under different dynamic conditions. Based on these results, the contributions of each parameter in the variation of the dynamic error attributes are estimated revealing many options to consider for building an efficient prediction model for error compensation. Neural network based prediction model suggests a promising performance.