3D Rough Surface Topography Model of Fractal Interpolation Based on Wavelet Transform

Kang, Mingxia; Tang, Wencheng; Zhang, Lu

doi:10.1088/1742-6596/1087/5/052031

Cited by 1 publication

(1 citation statement)

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“…The elimination of these negative effects can be helped by using the wavelet transformation, which has already been proven in many studies (see [36,37]) to perform better than the Fourier transformation. The wavelet transform was successfully used by Kang et al [38] to determine the fractal dimension of rough surfaces. The wavelet analysis can represent progress compared to the presented tests in two respects: on the one hand, it can determine the fractal dimension of the surface in the micro-and nano-roughness range with greater accuracy, and on the other hand, it can more accurately determine the boundary of the micro-and nano-region, which we were able to determine only in a relatively wide range of 0.196-1 µm.…”

Section: Discussionmentioning

confidence: 99%

Micro- and Nano-Roughness Separation Based on Fractal Analysis

Czifra,

Ancza

2024

Materials

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When describing the tribological behaviour of technical surfaces, the need for full-length scale microtopographic characterization often arises. The self-affine of surfaces and the characterisation of self-affine using a fractal dimension and its implantation into tribological models are commonly used. The goal of our present work was to determine the frequency range of fractal behaviour of surfaces by analysing the microtopographic measurements of an anodised aluminium brake plunger. We also wanted to know if bifractal and multifractal behaviour can be detected in real machine parts. As a result, we developed a new methodology for determining the fractal range boundaries to separate the nano- and micro-roughness. To reach our goals, we used an atomic force microscope (AFM) and a stylus instrument to obtain measurements in a wide frequency range (19 nm–3 mm). Power spectral density (PSD)-based fractal evaluation found that the examined surface could not be characterised by a single fractal dimension. A new method capable of separating nano- and micro-roughness has been developed for investigating multifractal behaviour. The presented procedure separates nano- and micro-roughness based on the geometric characteristics of surfaces. In this way, it becomes possible to specifically examine the relationship between the micro-geometry that can be measured in each wavelength range and the effects of cutting technology and the material structure that creates them.

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Section: Discussionmentioning

confidence: 99%