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CHATTER DETECTION IN MILLING PROCESS BASED ON TIME-FREQUENCY ANALYSIS

机译:基于时频分析的铣削加工颤振检测

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Chatter identification is necessary in order to achieve stable machining conditions. However, the linear approximation in regenerative chatter vibration is problematic because of the rich nonlinear characteristics in machining. In this study, a novel method to detect chatter is proposed. Firstly, measured cutting force signals are decomposed into a set of intrinsic mode functions by using ensemble empirical mode decomposition. Hilbert transform is following to extract the instantaneous frequency. Fast Fourier transform is also utilized for each intrinsic mode function to determine the intrinsic mode function that contains rich chatter. Finally, the standard deviation and energy ratio in frequency domain of intrinsic mode functions are found as simply dimensionless chatter indicators. The effectively proposed approach is validated by analyzing the machined surface topography and also compared to the stability lobe diagram.
机译:为了获得稳定的加工条件,必须进行振颤识别。然而,由于在加工中具有丰富的非线性特性,因此在再生颤振中的线性近似是有问题的。在这项研究中,提出了一种检测颤动的新方法。首先,通过整体经验模式分解将测得的切削力信号分解为一组固有模式函数。希尔伯特变换跟随以提取瞬时频率。快速傅立叶变换还用于每个本征模式函数,以确定包含丰富颤动的本征模式函数。最后,本征函数的频域中的标准偏差和能量比被视为简单的无量纲颤动指标。通过分析机加工表面形貌验证了有效提出的方法,并将其与稳定性凸角图进行了比较。

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