A review of static and dynamic analysis of ball screw feed drives, recirculating linear guideway, and ball screw

滚珠丝杠 非线性系统 运动学 球(数学) 刚度 机械工程 机床 工程类 振动 计算机科学 结构工程 数学 螺母 数学分析 物理 经典力学 量子力学
作者
Changyou Li,Mengtao Xu,Wenjun Song,Hongzhuang Zhang
出处
期刊:International Journal of Machine Tools & Manufacture [Elsevier]
卷期号:188: 104021-104021 被引量:63
标识
DOI:10.1016/j.ijmachtools.2023.104021
摘要

Static and dynamic analysis of key structural components of the machine tool is the crucial stage in transferring the physical to the virtual domain for digital manufacturing trends. The modeling technique of rolling kinematic joints with high nonlinearity can directly influence the accuracy and efficiency of prediction. Existing literature replicates the nonlinear static and dynamic characteristics considering the rolling element contact interface and proposes the theoretical modeling approach for the feed drives. However, there is a lack of systematic literature surveys. This paper reviews the current progress placed at the nonlinear analytical model of rolling kinematic joints, including ball screw feed drives, recirculating linear guideways, and ball screws. Advanced investigations on nonlinear dynamic stiffness and vibration response associated with ball screw feed drives are covered. Specifically, for linear guideways and ball screws, the stiffness and load distribution models can be divided into two categories: with and without consideration of the component structural deformations. Moreover, the corresponding detailed modeling process is introduced. The time-dependent modeling principle highlighting the recirculation motion of rolling elements is summarized, and friction and wear behavior is briefly discussed. The paper ends with the current research advancement and scarcity and recommends promising modeling tendencies. Particularly, the modeling tendencies require integrated model research on ball screw feed drives considering the more detailed nonlinear joint. Moreover, a fusion of multi-physics parameters is expected to achieve the high-fidelity mechanical model of key structural components for intelligent manufacturing demand.
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