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Research Papers: Contact Mechanics

Exact Counting of Random Height Features of Product Surfaces

[+] Author and Article Information
M. A. Mohamed

Department of Mechanical Engineering, Arab Academy for Sciences and Technology, 3-A Mohamed Mazhar Street, Zamalek 11211, Cairo 12012, Egyptlogarithm48@hotmail.com

J. Tribol 130(3), 031402 (Jun 20, 2008) (6 pages) doi:10.1115/1.2913554 History: Received March 17, 2007; Revised March 28, 2008; Published June 20, 2008

Although many statistical parameters are readily derivable from the autocorrelation function, relevant computations make their acquisition infeasible if required for product surface roughness where such a function can only be expressed in its digital form. Presented is a semianalytical approach that significantly reduces numerical computations conventionally followed to obtain width-type statistics of surface topography from the height autocorrelation function (HACF). The approach is based on fitting the digital form of the HACF to an analytic damped cosine that can then be readily differentiated and integrated. The applicability and accuracy of the proposed approach are illustrated for sampled height data experimentally collected from real product surfaces. Comparison of results using both conventional and suggested approaches shows that analytic fitting of the HACF leads to a rich set of descriptive width-type statistics as accurate as but less time consuming than conventional numerical techniques.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Measured profile grade 3M No. 36

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Figure 2

Autocorrelation function of rough surface grade 3M No. 36

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Figure 3

Measured profile grade 3M No. 600

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Figure 4

Autocorrelation function of fine surface grade 3M No. 600

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