Kinematic and stochastic surface topography of workpiece made of Al7075 in flank milling
| Autor: | Zhao Ke, Xibin Wang, Rolf Hockauf, Zhibing Liu, Dongqian Wang, Wenxiang Zhao |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Polynomial regression
Surface (mathematics) 0209 industrial biotechnology Mechanical Engineering Gaussian Flank milling 020207 software engineering Geometry 02 engineering and technology Kinematics Surface finish Industrial and Manufacturing Engineering Dexel Physics::Geophysics Computer Science Applications symbols.namesake 020901 industrial engineering & automation Distribution (mathematics) Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering symbols Physics::Atmospheric and Oceanic Physics Software Geology |
| Zdroj: | The International Journal of Advanced Manufacturing Technology. 96:2735-2745 |
| ISSN: | 1433-3015 0268-3768 |
| DOI: | 10.1007/s00170-018-1709-3 |
| Popis: | In this paper, a method is given to predict the surface topography in flank milling based on the experiment data of Al7075. First, the kinematic topography of the machined surface is analyzed with dexel model by CutS. Then, the measured stochastic topography is described by four-distribution-moment Gaussian distribution and quadratic regression is used to fit the values. Abbott curve is applied in pseudo random number generation to create the simulated stochastic topography. Finally, the combination of the kinematic and stochastic topography is calculated by material removal simulations (MRS) and is used to predict the real measured topography. The results show that the roughness of the stochastic topography increases with an increased feed per tooth and depth of cut, and the combined topography mostly matches to the measured one within the proposed method. |
| Databáze: | OpenAIRE |
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