Geometric Error Identification and Compensation of Cradle-Type Rotary Axis in 5-Axis Machine Tool Using Multilateration Measurement

The precision of the cradle-type rotary axis in a 5-axis machine tool significantly impacts the accuracy of workpieces, such as thin-walled surfaces in the aerospace industry. However, the axis line of the cradle is virtual, making its geometric errors difficult to measure and identify efficiently. In this article, a geometric error identification and compensation method for cradle-type rotary axis in a 5-axis machine tool using multilateration measurement is proposed. The high-precision length data from the tracking interferometer is used for the iterative self-calibration, and the sampling points’ positions and system parameters are obtained. The sampling points’ position errors are first attributed to the cradle’s position-independent geometric errors (PIGEs) and then to the position-dependent geometric errors (PDGEs). The cradle’s geometric errors are considered in the 5-axis machine tool, and the error compensation values of each axis are calculated through inverse kinematics. The proposed method only takes 1 h to identify all geometric errors, making the measurement more convenient. Experimental results show that the identified cradle’s geometric errors are similar to the commercial identification software TRAC-CAL, with an angular positioning error deviation of $6.9~\mu $ rad. The cradle’s motion accuracy has significantly improved with error compensation. In particular, the cradle’s angular positioning error is reduced by 84%, indicating the effectiveness of the proposed method. An extended application in a rotary table is given, and its angular positioning error is reduced by 67%. The proposed method provides a reference for the study of efficient geometric error identification and applies to different conditions.