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

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    Date
    2026
    Author
    Wang, Chia-Pei
    Erkorkmaz, Kaan
    McPhee, John
    Engin, Serafettin
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    Abstract
    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.
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4316766
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