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contributor authorWang, Chia-Pei
contributor authorErkorkmaz, Kaan
contributor authorMcPhee, John
contributor authorEngin, Serafettin
date accessioned2026-08-23T08:34:56Z
date available2026-08-23T08:34:56Z
date copyright2026/05/01
date issued2026
identifier issn1087-1357
identifier othermanu-24-1708.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4316766
description abstractAbstract. 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.
publisherThe American Society of Mechanical Engineers (ASME)
titleIdentification of Flexible Joint Multibody Dynamic Models for Machine Tool Feed Drive Assemblies Via Inertial Measurement Unit and Computer Numerical Control Data
typeJournal Paper
journal volume148
journal issue5
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.4068487
journal fristpage393
journal lastpage396
page4
treeJournal of Manufacturing Science and Engineering:;2026:;volume( 148 ):;issue:005
contenttypeFulltext


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