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A Method for Identification of Machine-tool Dynamics under Machining

机译:一种识别机械加工机床动态的方法

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Dynamic properties of machine-tool structures are likely to change under machining conditions. Thus, the dynamic parameters obtained by traditional experimental modal analysis in the static state may not characterize accurately the dynamics of the machine tool structure in operation. This paper proposes a new method of so-called AEMA (Active Excitation Modal Analysis) to identify the dynamic modal parameters of a machine tool structure during machining. A random cutting excitation technique realized by cutting a specially designed workpiece is proposed to provide strong and evenly distributed excitation within the frequency range of interest. The surface of the workpiece has a long narrow random zigzag width, which randomizes the resulting cutting forces. The LSCE (Least Square Complex Exponential) method is employed to estimate the modal parameters from just the measured responses. Then an algorithm based on two novel tools, the harmonic frequency fence and the spectrum abruptness ratio, is presented to eliminate the harmonic modes attributed to AC power and rotation frequency. The abruptness ratio is used to detect the basic frequency, and then the fence filters out the harmonic modes caused by peaks at integer multiples of the basic frequency through narrow frequency fence slots followed by a damping ratio limit. Finally, the proposed AEMA method is experimentally validated and shows satisfactory results.
机译:机床结构的动态特性可能在加工条件下改变。因此,在静态状态下通过传统实验模态分析获得的动态参数可以在操作中准确地表征机床结构的动态。本文提出了一种新的AEMA(主动励磁模态分析)的新方法,以识别加工过程中机床结构的动态模态参数。提出了一种通过切割特定设计的工件而实现的随机切割激励技术,以在频率范围内提供强大且均匀分布的激励。工件的表面具有长窄的随机锯齿形宽度,其随机化了所得到的切割力。使用LSCE(最小二乘复杂的指数)方法来估计从测量的响应中的模态参数。然后,提出了一种基于两种新颖工具,谐波频率围栏和频谱突出比的算法,以消除归因于交流电源和旋转频率的谐波模式。突发比用于检测基本频率,然后围栏通过窄频率围栏槽通过窄频率限制来滤除由窄频率围栏的基本频率的整数倍数引起的谐波模式。最后,提出的AEMA方法是通过实验验证的,并显示令人满意的结果。

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