Estimation of Chatter Vibration Under End-Milling Process With a Wavelet Transform

Haruki Minetaka, Nobutoshi Ozaki, T. Hirogaki, E. Aoyama
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Abstract

In this study, a new analysis method using a wavelet transform was considered to evaluate the chatter vibration generated during end milling. End milling often generates vibrations between the tool and work material, called chatter vibration, which causes deterioration of the finished surface and breakage of the tool. Therefore, countermeasures to detect chatter vibration at an early stage have been attempted in the past by using fast Fourier transform (FFT) and short-time Fourier transform (STFT) methods and monitoring the dynamic stability of the cutting process. However, the FFT analysis method assumes steady-state vibration, and the STFT method does not have sufficient frequency resolution. In contrast, the wavelet transform is excellent for analyzing non-stationary vibrations and has a high noise separation capability. To fully validate the analysis method, a groove was added to the machined surface, so that the cutting condition changed with time, and the cutting vibration under the condition where the disturbance was involuntary was analyzed. As a result, it was possible to identify minute fluctuations in chatter vibration, which could not be obtained using the STFT method.
用小波变换估计立铣削过程中的颤振
提出了一种基于小波变换的立铣削颤振分析方法。立铣削常常在刀具和工件材料之间产生振动,称为颤振振动,这种振动会导致加工表面的劣化和刀具的断裂。因此,过去已经尝试使用快速傅里叶变换(FFT)和短时傅里叶变换(STFT)方法在早期检测颤振,并监测切削过程的动态稳定性。然而,FFT分析方法假设的是稳态振动,STFT方法没有足够的频率分辨率。相比之下,小波变换在分析非平稳振动方面表现优异,并且具有较高的噪声分离能力。为了充分验证分析方法,在加工表面加槽,使切削条件随时间变化,分析非自愿扰动条件下的切削振动。因此,可以识别颤振中的微小波动,这是使用STFT方法无法获得的。
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