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    Exact Counting of Random Height Features of Product Surfaces

    Source: Journal of Tribology:;2008:;volume( 130 ):;issue: 003::page 31402
    Author:
    M. A. Mohamed
    DOI: 10.1115/1.2913554
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: 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.
    keyword(s): Surface roughness , Waves , Computation , Fittings , Stochastic processes , Wavelength , Spectra (Spectroscopy) , Density , Modeling AND Probability ,
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      Exact Counting of Random Height Features of Product Surfaces

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    http://yetl.yabesh.ir/yetl1/handle/yetl/139384
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    contributor authorM. A. Mohamed
    date accessioned2017-05-09T00:30:38Z
    date available2017-05-09T00:30:38Z
    date copyrightJuly, 2008
    date issued2008
    identifier issn0742-4787
    identifier otherJOTRE9-28759#031402_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/139384
    description abstractAlthough 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.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleExact Counting of Random Height Features of Product Surfaces
    typeJournal Paper
    journal volume130
    journal issue3
    journal titleJournal of Tribology
    identifier doi10.1115/1.2913554
    journal fristpage31402
    identifier eissn1528-8897
    keywordsSurface roughness
    keywordsWaves
    keywordsComputation
    keywordsFittings
    keywordsStochastic processes
    keywordsWavelength
    keywordsSpectra (Spectroscopy)
    keywordsDensity
    keywordsModeling AND Probability
    treeJournal of Tribology:;2008:;volume( 130 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian