基于特征工件的五轴数控机床动静态误差辨识与分离方法
Dynamic and Static Error Identification and Separation Method for Five-Axis CNC Machine Tools Based on Feature Workpiece

数控机床是工业生产的重要场所，但因其误差项多，出现残次品，浪费社会资源。因此，测量机床误差，提高其精度显得极为重要。而现有机床误差测量方法中，基于仪器测量的方法不仅耗时、仪器成本高，且不以实际切削工件为误差参考源；基于切削特征试件方法未将误差源进行分离。针对上述问题，本文提出了基于特征工件切削的动静态误差高效辨识与分离方法。本文设计并切削可反映几何误差的特征工件，分别对其进行在机测量和三坐标测量机标定，基于两组测试数据实现15项几何误差与动态误差的辨识与分离。通过空间误差模型，将辨识与分离得到的误差补偿到数控系统，新切削的特征工件精度提高约50%，证实了本方法的可行性、高效性和准确性。
CNC machine tools are an important place for industrial production. However, due to its many error items, defective products appear, which wastes social resources. Therefore, it is extremely im-portant to measure machine tool errors and improve their accuracy. Among the existing measure-ment methods, the method based on instrument measurement is not only time-consuming and high in instrument cost, but also does not take the actual cutting workpiece as an error reference source. The method based on the cutting characteristics of the specimen does not separate the error sources. To solve the above problems, this paper proposes an efficient identification and separation method of dynamic and static errors based on the cutting of characteristic workpiece. Characteristic workpiece is designed and cut that can reflect geometric errors. Perform on-machine measurement and three-coordinate measuring machine calibration respectively. Based on two sets of test data, 15 geometric errors and dynamic errors are identified and separated. Through the spatial error model, the error obtained from identification and separation is compensated to the numerical control sys-tem. The accuracy of newly cut feature workpiece is increased by about 50%, which proves the fea-sibility, efficiency and accuracy of this method.