The chatter phenomenon shows the dynamic characteristics of tool vibration in the endmilling process and will change according to the irregular dynamic characteristics of that tool vibration. This chatter produces an adverse effect on tool life, machining integrity, surface quality of the workpiece, and other geometric accuracy. Chatter behaviour in endmilling is a complex, non-linear phenomenon, which is very difficult to detect and diagnose. It is therefore necessary to suggest a new method for analysing chatter mechanics. This paper presents a new method for the detection of chatter in the endmilling operation based on the wavelet transform. This wavelet transform method provides various ways to determine chatter characteristics. The fundamental coefficient property of the wavelet transform is reviewed. The reliability of the wavelet transform method is verified by comparing the spectra using the fast Fourier transform (FFT). The behaviour of the detail coefficients obtained by wavelet transform reveals the possibility to detect and analyse chatter and other malfunction states using tool dynamometer cutting force. Because wavelets are closely related to filter, the method presented in this paper can be applied to other real-time cutting force monitoring and analysis in a range of endmilling processes.
For the investigation of the chatter modes, the power spectrum of the parametric time series model was adopted and analyzed at several mixed conditions of different revolution. This paper describes a methodology for an application of several time series such as AR (forward-backward, burg, least square, Yule Walker, geometric lattice, instrumental variable), ARX (least square, instrumental variable), ARMAX, ARMA., Box Jenkins, Output Error. To estimate the chatter mode using their spectral analysis their results were compared with one another. As a result, it was proven that several time series methods can be used for chatter mode estimation. Among them, the ARX, ARMAX and instrumental variable methods (iv4) are more desirable and reliable than the other algorithm for the exact calculation of the chatter mode in endmilling. Among three cutting forces, the z direction cutting force, Fz, has more powerful characteristics of chatter occurring than the cutting forces, Fx and Fy, in the sense that weak mode is calculated exactly and there is no shifted or pseudo mode in the estimated power spectra of endmilling forces.
There are many modelling methods using theoretical and experimental data. Recently,
fractal interpolation methods have been widely used to estimate and analyse various data. Due to the
chaotic nature of dynamic roundness profile data in roundness, some desirable method must be used
for the analysis of data which is natural to sequential data. Fractal analysis used in this paper is within
the scope of the fractal interpolation and fractal dimension. Also, two methods for computing the
fractal dimension have been introduced, which can calculate the fractal dimension of typical dynamic
roundness profile data according to the number of data points in which the fixed data are generally
lower than 120 data points. This fractal analysis shows a possible prediction and analysis of roundness
profile that has some different roundness profile in round shape operation such as cylindrical grinding,
turning, drilling and boring.
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