首页> 外文期刊>Wear: an International Journal on the Science and Technology of Friction, Lubrication and Wear >Multiscale characterisation of 3D surface topography of DLC coated and uncoated surfaces by directional blanket covering (DBC) method
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Multiscale characterisation of 3D surface topography of DLC coated and uncoated surfaces by directional blanket covering (DBC) method

机译:方向毯覆盖(DBC)方法DLC涂层和未涂覆表面3D表面形貌的多尺度表征

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摘要

Diamond-like carbon (DLC) coated surfaces exhibit anisotropic and multi-scale characteristics, i.e., their roughness change with both scale and direction. However, most currently used standard surface characterisation parameters and methods work well only with isotropic surfaces at a single scale. This problem can be overcome by variance orientation transform (VOT) and directional blanket covering (DBC) methods. Both methods calculate fractal signatures (FSs) in different directions allowing for detailed measurement of roughness of anisotropic and multiscale surfaces. FS is a set of fractal dimensions (FDs) at individual scales, and FD is a measure of surface roughness. High FD values mean rougher surfaces. Unlike other directional FSs methods, e.g., VOT, the DBC method automatically selects scales of calculations. In this study, the DBC method was used to analyse surface topography images of DLC coated and uncoated bearing steel discs of increasing roughness. Its ability to differentiate between two groups of surfaces is evaluated. The results obtained showed that the DBC method can detect differences in roughness at different scales and directions between the DLC coated and uncoated surfaces. This work could lead to applications of the DBC method in modelling of wear and friction behaviour of DLC coated and uncoated surfaces at different scales. (C) 2017 Elsevier B.V. All rights reserved.
机译:菱形碳(DLC)涂覆表面表现出各向异性和多尺度特性,即它们的粗糙度随着比例和方向而变化。然而,最目前使用的标准表面表征参数和方法仅用单一刻度的各向同性表面工作。可以通过方差定向变换(VOT)和方向毯覆盖(DBC)方法来克服此问题。两种方法在不同方向上计算分形签名(FSS),允许详细测量各向异性和多尺度表面的粗糙度。 FS是各个刻度的一组分形尺寸(FDS),FD是表面粗糙度的量度。高FD值意味着粗糙的表面。与其他定向FSS方法不同,例如VOT,DBC方法自动选择计算尺度。在本研究中,DBC方法用于分析DLC涂覆和未涂覆的轴承钢盘的表面形貌图像,增加粗糙度。它评估其在两组表面之间区分的能力。得到的结果表明,DBC方法可以检测DLC涂覆和未涂覆的表面之间不同刻度和方向上的粗糙度的差异。该工作可能导致DBC方法在不同尺度下DLC涂覆和未涂层表面的磨损和摩擦行为建模中的应用。 (c)2017 Elsevier B.v.保留所有权利。

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