AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Home Friction Article
PDF (3.1 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Truncated separation method for characterizing and reconstructing bi-Gaussian stratified surfaces

Songtao HU1Weifeng HUANG1Noel BRUNETIERE2Xiangfeng LIU1( )Yuming WANG1
 State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
 Institut Pprime, CNRS-Universite de Poitiers-ENSMA, Futuroscope Chasseneuil Cedex 86962, France
Show Author Information

Abstract

Existing ISO segmented and continuous separation methods for differentiating the two components contained within a bi-Gaussian stratified surface were developed based on the fit of the probability material ratio curve. In the present study, because of the significant effect of the plateau component on tribological behavior such as asperity contact, wear and friction, a truncated separation method is proposed based on the truncation of the upper Gaussian component defined by zero skewness. The three separation methods are applied to real worn surfaces. Surface-separation and surface-reconstruction results show that the truncated method accurately captures the upper component identically to the ISO and continuous ones. The identification of the lower component characteristics requires performing a curve fit procedure on the data left after truncation. However, the truncated method fails in identifying the upper component when the material ratio of the transition is less than 9%.

References

[1]
Whitehouse D J. Surfaces-a link between manufacture and function. Proc Inst Mech Eng 192: 179-188 (1978)
[2]
Hu S, Brunetiere N, Huang W, Liu X, Wang Y. Continuous separating method for characterizing and reconstructing bi-Gaussian stratified surfaces. Tribol Int 102: 454-452 (2016)
[3]
Minet C, Brunetiere N, Tournerie B, Fribourg D. Analysis and modeling of the topography of mechanical seal faces. Tribol Trans 53: 799-815 (2010)
[4]
Whitehouse D J. Assessment of surface finish profiles produced by multi-process manufacture. Proc the Inst Mech Eng Part B: J Eng Manufact 199: 263-270 (1985)
[5]
Malburg M C, Raja J, Whitehouse D J. Characterization of surface texture generated by plateau honing process. CIRP Annals-Manufacturing Technology 42: 637-639 (1993)
[6]
Sannareddy H, Raja J, Chen K. Characterization of surface texture generated by multi-process manufacture. Int J Mach Tools Manufact 38: 529-536 (1998)
[7]
Leefe S E. Bi-Gaussian’ representation of worn surface topography in elastic contact problems. Tribol Ser 34: 281-290 (1998)
[8]
Pawlus P, Grabon W. The Method of Truncation parameters measurement from material ratio curve. Prec Eng 32: 342-347 (2008)
[9]
Hu S, Huang W, Brunetiere N, Song Z, Liu X, Wang Y. Stratified effect of continuous bi-Gaussian rough surface on lubrication and asperity contact. Tribol Int 104: 328-341 (2016)
[10]
Hu S, Brunetiere N, Huang W, Liu X, Wang Y. Stratified revised asperity contact model for worn surfaces. J Tribol in press, (2016)
[11]
Abbot E J, Firestone F A. Specifying surface quality. Mech Eng 55: 569-578 (1933)
[12]
Surface texture: Profile method; surfaces having stratified functional properties—Part 2: Height characterization using the linear material ratio curve. ISO 13565-2, 1996.
[13]
Surface texture: Profile method; surfaces having stratified functional properties—Part 3: Height characterization using the material probability curve. ISO 13565-3, 1998.
[14]
Williamson J P B. Microtopography of surfaces. Proc Inst Mech Eng 182: 21-30 (1985)
[15]
Staufert G. Characterization of random roughness profiles —A comparison of AR-modeling technique and profile description by means of commonly used parameters. Annals of the CIRP 28: 431-435 (1979)
[16]
DeVries W R. Autoregressive time series models for surface profile characterization. Annals of the CIRP 28: 437-440 (1979)
[17]
Whitehouse D J. The generation of two dimensional random surfaces having a specified function. Annals of the CIRP 32: 495-498 (1983)
[18]
Patir N. A Numerical method for random generation of rough surfaces. Wear 47: 263-277 (1978)
[19]
Bakolas V. Numerical generation of arbitrarily oriented non-Gaussian three-dimensional rough surfaces. Wear 254: 546-554 (2004)
[20]
Hu Y Z, Tonder K. Simulation of 3-D random rough surface by 2-D digital filter and Fourier analysis. Int J Mach Tools Manufact 32: 83-90 (1992)
[21]
Majumdar A, Tien C. Fractal characterization and simulation of rough surfaces. Wear 136: 313-327 (1990)
[22]
Wu J. Simulation of rough surfaces with FFT. Tribol Int 33: 47-58 (2000)
[23]
Wu J. Simulation of non-Gaussian surfaces with FFT. Tribol Int 37: 339-346 (2004)
[24]
Johnson N L. Systems of frequency curves generated by method of translation. Biometrika 36: 149-176 (1949)
[25]
Watson W, Spedding T A. The time series modelling of non-Gaussian engineering processes. Wear 83: 215-231 (1982)
[26]
Hill I D, Hill R, Holder R L. Fitting Johnson curves by moments. Applied Statistics 25: 180-189 (1976)
[27]
Francisco A, Brunetiere N. A Hybrid method for fast and efficient rough surface generation. IMechE Part J: J Eng Tribol 230: 747-768 (2016)
[28]
Pawlus P. Simulation of stratified surface topographies. Wear 264: 457-463 (2008)
[29]
Tomescu A. Simulation of surface roughness for tribological applications. Master thesis. Universite de Poitiers, Poitiers, France, 2012.
Friction
Pages 32-44
Cite this article:
HU S, HUANG W, BRUNETIERE N, et al. Truncated separation method for characterizing and reconstructing bi-Gaussian stratified surfaces. Friction, 2017, 5(1): 32-44. https://doi.org/10.1007/s40544-016-0129-3

530

Views

12

Downloads

21

Crossref

N/A

Web of Science

22

Scopus

0

CSCD

Altmetrics

Received: 13 July 2016
Revised: 21 September 2016
Accepted: 03 November 2016
Published: 07 March 2017
© The author(s) 2016

This article is published with open access at Springerlink.com

Return