自然科学版 英文版
自然科学版 英文版
自然科学版 英文版

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中南大学学报(英文版)

Journal of Central South University

Vol. 24    No. 1    January 2017

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Modeling of rough surfaces with given roughness parameters
ZHOU Wei(周炜)1, TANG Jin-yuan(唐进元)2, 3, HE Yan-fei(何艳飞)2, 3, ZHU Cai-chao(朱才朝)4

1. Intelligent Manufacturing Institute (Hunan Provincial Key Laboratory of High Efficiency and Precision Machining of Difficult-to-Cut Material), Hunan University of Science and Technology,Xiangtan 411201, China;
2. State Key Laboratory of High Performance Complex Manufacturing, Central South University,Changsha 410083, China;
3. School of Mechanical and Electrical Engineering, Central South University, Changsha 410083,China;
4. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044,China

Abstract:Modeling of rough surfaces with given roughness parameters is studied, where surfaces with Gaussian height distribution and exponential auto-correlation function (ACF) are concerned. A large number of micro topography samples are randomly generated first using the rough surface simulation method with FFT. Then roughness parameters of the simulated roughness profiles are calculated according to parameter definition, and the relationship between roughness parameters and statistical distribution parameters is investigated. The effects of high-pass filtering with different cut-off lengths on the relationship are analyzed. Subsequently, computing formulae of roughness parameters based on standard deviation and correlation length are constructed with mathematical regression method. The constructed formulae are tested with measured data of actual topographies, and the influences of auto-correlation variations at different lag lengths on the change of roughness parameter are discussed. The constructed computing formulae provide an approach to active modeling of rough surfaces with given roughness parameters.

 

Key words: micro topography; rough surface; roughness; active modeling

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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