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Reverse identification of dynamic and static motion errors for five-axis machine based on specimen feature
Hainan Zhang1, Sitong Xiang1, Chao Liu1
1Faculty of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China.
Abstract:
The dynamic and static error motions dramatically influence the accuracy of five-axis machine tools. We propose a new approach of reverse identification for dynamic and static motion error of five-axis machine tools through specimen cutting and feature decomposition. The error mapping between the workpiece features and the corresponding errors is established, and a feature specimen is designed accordingly. By measuring the specimen with the on-machine measurement and CMM, 15 static motion errors and dynamics-induced errors can be identified and separated. The error estimates are verified by the direct measurement via the interferometer, autocollimator and ballbar tests. These errors are compensated using a volumetric error model, and the specimen accuracy after compensation is effectively increased, which confirms the feasibility and accuracy of this method.
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