Machining error compensation based on a compliance error model reconstructed surface method

Author:

Chen Yueping1ORCID,Yu Shifang,Tang Qingchun,Zeng Linan

Affiliation:

1. Guangxi University of Science and Technology

Abstract

Abstract To reduce the errors caused by the overall compliance of the system and the machine tool wear during the machining process for curved workpieces, and to improve the machining accuracies of curved workpieces, a machining error compensation method using a compliance error model to reconstruct the surface was adopted. During a process involving multiple cuts, on-machine measurement (OMM) was achieved by replacing the cutting tool with a touch probe. After the last semi-finishing cut, the error values were measured and compensated for using a compliance error model that predicted the change in the overall compliance of the system and estimated the error at the finishing cut depth based on the measured machining error at the previous cut depth. Finally, the machining errors before and after compensation of formula and free-form surface workpieces were verified experimentally. For the formula surface workpiece, the maximum value of the machining error was reduced from 0.057 mm to 0.0163 mm, and the average absolute value of the machining error was reduced from 0.047 mm to 0.0032 mm after compensation when using the method based on a compliance error model reconstructed surface. For the free-form surface workpiece, the maximum value of the machining error was reduced from 0.0586 mm to 0.0166 mm, and the average absolute value of the machining error was reduced from 0.0483 mm to 0.0057 mm after compensation using the compliance error model reconstructed surface method. It was verified that this method could effectively reduce machining errors and improve the machining accuracy of machine tools. This method can be used to predict and compensate for machining errors at different cut depths, which is of great research significance for machining various types of curved workpieces.

Publisher

Research Square Platform LLC

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