scholarly journals Characterization and Functional Evaluation of Surface Texture of Micro Eccentric Shaft Based on Multi-index

2021 ◽  
Author(s):  
Minghui Cheng ◽  
Li Jiao ◽  
Pei Yan ◽  
Zhongke Niu ◽  
Tianyang Qiu ◽  
...  
Keyword(s):  
Surface Texture ◽  
End Milling ◽  
Cutting Tools ◽  
Dynamic State ◽  
High Tech ◽  
Functional Evaluation ◽  
Height Distribution ◽  
Milling Cutter ◽  
Eccentric Shaft ◽  
Flat End Milling

Abstract Micro eccentric shaft has important application in many high-tech fields because of its small specific gravity, material and energy saving. The surface texture generated during processing has an indispensable influence on the surface integrity and the final functional capability. However, due to the micro scale and weak rigidity, it is difficult to characterize the surface texture and evaluate the functionality by traditional quantitative parameters. In order to comprehensively realize the surface texture characterization and functional analysis, a mathematical model is established to analyze the surface texture machined with different cutting tools. AnchorThe machining deformation of the micro eccentric shaft machined during turn-milling with different cutting tools is compensated. Then the surface microscopic profile and functional performance of the surface texture are analyzed by amplitude distribution function (ADF) and bearing area curve (BAC), and the surface texture is also evaluated by fractal dimension, which can avoid the effect of scale and resolution. Furthermore, power spectrum density (PSD) is utilized to analyze the relationship between the process dynamic state and geometrical specification of the surface texture. It is shown that the microscopic height distribution of surface machined by flat end milling cutter tends to be more random and there are more microscopic geometric features than that of the ball end milling cutter. The machined surface obtained by the flat end milling cutter has better load bearing, wear resistance and liquid retention capability.

Directionally Independent Failure Prediction of End-Milling Tools During Pocketing Maneuvers

2007 ◽  
Vol 129 (4) ◽  
pp. 770-779 ◽  
Author(s):  
Christopher A. Suprock ◽  
Joseph J. Piazza ◽  
John T. Roth
Keyword(s):  
Discrete Cosine Transform ◽  
End Milling ◽  
Cutting Tools ◽  
Primary Component ◽  
Operating Conditions ◽  
Frequency Method ◽  
Cosine Transform ◽  
Impending Fracture ◽  
Triaxial Dynamometer ◽  
Acceleration Signals

Tracking the health of cutting tools under typical wear conditions is advantageous to the speed and efficiency of manufacturing processes. Existing techniques monitor tool performance through analyzing force or acceleration signals whereby prognoses are made from a single sensor type. This work proposes to enhance the spectral output of autoregressive (AR) models by combining triaxial accelerometer and triaxial dynamometer signals. Through parallel processing of force and acceleration signals using single six degree of freedom modeling, greater spectral resolution is achieved. Two entirely independent methods of tracking the tool wear are developed and contrasted. First, using the discrete cosine transform, primary component analysis will be applied to the spectral output of each AR auto and cross spectrum (Method 1). Each discrete cosine transform of the six-dimensional spectral data is analyzed to determine the magnitude of the critical (primary) variance energy component of the respective spectrum. The eigenvalues of these selected spectral energies are then observed for trends toward failure. The second method involves monitoring the eigenvalues of the spectral matrices centered at the toothpass frequency (Method 2). The results of the two methodologies are compared. Through the use of the eigenvalue method, it is shown that, for straight and pocketing maneuvers, both methods successfully track the condition of the tool using statistical thresholding. The techniques developed in this work are shown to be robust by multiple life tests conducted on different machine platforms with different operating conditions. Both techniques successfully identify impending fracture or meltdown due to wear, providing sufficient time to remove the tools before failure is realized.

Paper 17: Microtopography of Surfaces

1967 ◽  
Vol 182 (11) ◽  
pp. 21-30 ◽  
Author(s):  
J. B. P. Williamson
Keyword(s):  
Gaussian Distribution ◽  
Contact Area ◽  
Surface Texture ◽  
Glass Surface ◽  
Surface Density ◽  
Radius Of Curvature ◽  
Height Distribution ◽  
Digital Analysis ◽  
Texture Parameters ◽  
Combining Data

This paper describes an approach to the study of surfaces based on the digital analysis of data obtained from profilometric examinations. This technique is used to determine several new surface texture parameters, including the surface density, height distribution, and mean radius of curvature of the asperities. Recent theories have shown that these are the parameters which control the nature of surface contact. The implications which these ideas have for the science of metrology are discussed. The study also shows that many surfaces have height distributions which are Gaussian, and in particular that the heights of the upper half of most surfaces closely follow a Gaussian distribution. By combining data obtained from many closely spaced parallel profiles it has been possible to reconstruct detailed maps of the surface texture. Two examples are discussed: bead-blasted aluminium, and a glass surface lightly blasted with alumina. One of the advantages of microcartography is that it permits the geometry of the contact between rough surfaces to be studied in detail. A map is given showing the manner in which the contact area between two bead-blasted aluminium surfaces splits into sub-areas, and how these sub-areas are distributed with respect to the surface features of the contacting solids.

scholarly journals Optimization of Texture Density Distribution of Carbide Alloy Micro-Textured Ball-End Milling Cutter Based on Stress Field

2020 ◽  
Vol 10 (3) ◽  
pp. 818
Author(s):  
Minli Zheng ◽  
Chunsheng He ◽  
Shucai Yang
Keyword(s):  
Wear Resistance ◽  
Stress Field ◽  
Density Distribution ◽  
Titanium Alloys ◽  
Contact Area ◽  
End Milling ◽  
Variable Density ◽  
Milling Cutter ◽  
Ball End Milling ◽  
Texture Density

The insertion of micro-textures plays a role in reducing friction and increasing wear resistance of the cutters, which also has a certain impact on the stress field of the cutter during milling. Therefore, in order to study the mechanisms of friction reduction and wear resistance of micro-textured cutters in high speed cutting of titanium alloys, the dynamic characteristics of the instantaneous stress field during the machining of titanium alloys with micro-textured cutters were studied by changing the distribution density of the micro-textures on the cutter. First, the micro-texture insertion area of the ball-end milling cutter was theoretically analyzed. Then, variable density micro-textured ball-end milling cutters and non-texture cutters were used to cut titanium alloy, and the mathematical model of milling force and cutter-chip contact area was established. Then, the stress density functions of different micro-texture density cutters and non-texture cutters were established to simulate the stress fields of variable density micro-textured ball-end milling cutters and non-texture cutters. Finally, the genetic algorithm was used to optimize the variable density distribution of micro-textured cutters in which the instantaneous stress field of the cutters was taken as the optimization objective. The optimal solution for the variable density distribution of the micro-textured cutter in the cutter-chip tight contact area was obtained as follows: the texture distribution densities in the first, second, and third areas are second, and third areas are 0.0905, 0.0712, and 0.0493, respectively.

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