Analysis Method of Chatter Vibration by Two-dimensional Fourier Transform of the Image of the End Milling Curved Surface

2020 ◽  
Vol 2020.95 (0) ◽  
pp. 01_102
Author(s):  
Nobutoshi OZAKI ◽  
Shota MATSUI ◽  
Haruki MINETAKA ◽  
Soriano Carlos ◽  
Toshiki HIROGAKI ◽  
...  
2021 ◽  
Author(s):  
Haruki Minetaka ◽  
Nobutoshi Ozaki ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama

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.


2016 ◽  
Vol 874 ◽  
pp. 423-428
Author(s):  
Kaito Aotani ◽  
Ryosuke Shiota ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama

Chatter vibration in end milling remains a serious problem for manufacturing engineers. Chatter vibration often leaves a characteristic pattern or chatter mark on the machined surface. Chatter marks are generated by the relative displacement of the tool and the workpiece. Closer observation of chatter marks may prove useful in understanding chatter vibration. In this study, we investigated chatter mark patterns on end-milled surfaces. Based on these observations, we proposed and demonstrated the effectiveness of an iterative analysis method to identify stable machining conditions and minimize chatter vibration in various operations without use of sensors under specific conditions.


Author(s):  
L. Reimer ◽  
R. Oelgeklaus

Quantitative electron energy-loss spectroscopy (EELS) needs a correction for the limited collection aperture α and a deconvolution of recorded spectra for eliminating the influence of multiple inelastic scattering. Reversely, it is of interest to calculate the influence of multiple scattering on EELS. The distribution f(w,θ,z) of scattered electrons as a function of energy loss w, scattering angle θ and reduced specimen thickness z=t/Λ (Λ=total mean-free-path) can either be recorded by angular-resolved EELS or calculated by a convolution of a normalized single-scattering function ϕ(w,θ). For rotational symmetry in angle (amorphous or polycrystalline specimens) this can be realised by the following sequence of operations :(1)where the two-dimensional distribution in angle is reduced to a one-dimensional function by a projection P, T is a two-dimensional Fourier transform in angle θ and energy loss w and the exponent -1 indicates a deprojection and inverse Fourier transform, respectively.


2020 ◽  
Vol 12 (8) ◽  
pp. 168781402093046 ◽  
Author(s):  
Noor Saeed Khan ◽  
Qayyum Shah ◽  
Arif Sohail

Entropy generation in bioconvection two-dimensional steady incompressible non-Newtonian Oldroyd-B nanofluid with Cattaneo–Christov heat and mass flux theory is investigated. The Darcy–Forchheimer law is used to study heat and mass transfer flow and microorganisms motion in porous media. Using appropriate similarity variables, the partial differential equations are transformed into ordinary differential equations which are then solved by homotopy analysis method. For an insight into the problem, the effects of various parameters on different profiles are shown in different graphs.


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