Identification of Flexible Joint Multibody Dynamic Models for Machine Tool Feed Drive Assemblies Via Inertial Measurement Unit and Computer Numerical Control Data

Abstract High-accuracy modeling of machine tool dynamics is essential for advanced process planning and monitoring. However, modeling high-speed multi-axis machines is challenging due to the inherent coupled and nonlinear multibody dynamics and structural flexibility. This complex modeling task is addressed by a new approach in which the control dynamics and the open-loop plant dynamics are characterized by a multiple-input and multiple-output (MIMO) linear time-invariant (LTI) system coupled with a generalized disturbance, which is able to capture the open-loop coupled nonlinear dynamics. As a case study, different machine tool topologies of a flexible linear drive coupled with a rotary drive are systematically analyzed using the proposed modeling approach. The identification procedure for the proposed method requires capturing the internal structural vibration between the drives. This article also presents a method to reconstruct the internal structural vibration using data from the embedded encoders as well as a low-cost microelectromechanical systems (MEMS) inertial measurement unit (IMU) mounted on the machine table. This modeling-building approach is nonintrusive and practical for industrial implementation. The experimental validation shows a 2–6% error in predicting the tracking error and motor force/torque. Especially, the vibratory inter-axis coupling effect and posture-dependency are accurately predicted.