Modeling of the dynamic behavior of machine tools: influences of damping, friction, control and motion

Modeling of the dynamic behavior of machine tools: influences of damping, friction, control and motion
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DOI:
10.1007/s11740-016-0704-5
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发表时间:
2017-02
期刊:
Production Engineering
影响因子:
--
通讯作者:
C. Rebelein;J. Vlacil;M. Zäh
C. Rebelein;J. Vlacil;M. Zäh
中科院分区:
其他
文献类型:
--
作者:
C. Rebelein;J. Vlacil;M. Zäh

文献摘要

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在设计机床的过程中,需要虚拟模型来预测动态行为并优化机床性能。为此,在模拟中必须考虑不同的影响因素,例如质量、刚度和阻尼特性以及摩擦力、进给驱动控制和运动。然而,通常没有适合所有这些不同影响因素的模型和建模方法。本文针对上述影响因素提供了模型。随后,提出了一种建模方法,可以高精度预测动态行为。通过使用这种建模方法,可以研究和评估影响因素对机床振动行为的影响。非线性摩擦力和线性耗散源对阻尼行为影响最大。相比之下,进给驱动控制对振动行为的影响较小。运动可以极大地影响振动行为。它们的影响主要限于进给驱动器的轴向模式。在这些模式下,运动时的阻尼比与静止时相比可变化高达 ±35%。有了这些见解以及所提出的模型和建模方法,就出现了预测和优化机床动态行为的新可能性,从而提高了机床性能。
In the process of designing a machine tool virtual models are required to predict the dynamic behavior and optimize the machine tool performance. For this purpose, the different influencing factors mass, stiffness and damping properties as well as friction forces, feed drive controls and movements have to be considered in the simulation. However, usually no suitable models and modeling approaches are available for all of these various influencing factors. In this paper, models are provided for the mentioned influencing factors. Subsequently, a modeling approach is proposed, which allows to predict the dynamic behavior with high accuracy. By using this modeling approach, the influencing factors are investigated and evaluated with regard to their effects on the vibration behavior of a machine tool. The nonlinear friction forces and the linear dissipation sources have the greatest impact on the damping behavior. In comparison, the impact of the feed drive control on the vibration behavior is low. Movements can greatly influence the vibration behavior. Their effects are mainly restricted to the axial modes of the feed drives. At these modes, the damping ratios can vary under motion by up to ±35% compared to a standstill. With these insights and the proposed models and modeling approaches new possibilities arise to predict and optimize the dynamic behavior of a machine tool and thus to enhance the machine tool performance.