Details
| Original language | English |
|---|---|
| Pages (from-to) | 365-373 |
| Number of pages | 9 |
| Journal | Technisches Messen |
| Volume | 83 |
| Issue number | 6 |
| Publication status | Published - 4 Jun 2016 |
Abstract
In this article, fractal analysis combined with roughness measurement is proposed to characterize the new generations of HVOF sprayed coatings' surface textures. Two-dimensional and three-dimensional box counting algorithms are introduced to determine the fractal dimension, which is considered as a scale-invariant parameter and is able to describe chaos and complexity of the surface. For surface roughness metrology, a confocal laser scanning microscope with different lenses is used to acquire the areal topography, providing a sequence of height maps with different image resolutions. Typical areal roughness parameters are assessed based on the international standard ISO-25178. The results show that the fractal dimension is a powerful tool to depict the nature of the surface texture of the investigated coatings. Moreover, it is found that the traditional amplitude roughness parameters depend strongly on the range of the measurement field as well as the datasets' resolution, whereas the fractal dimension is rather invariant to the scales of the measured datasets. Finally, the correlation between the fractal dimension and roughness parameters is given at the end of this paper.
Keywords
- box-count algorithm, Fractal analysis, new HVOF sprayed coating, optical metrology, roughness measurement
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Instrumentation
- Engineering(all)
- Electrical and Electronic Engineering
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In: Technisches Messen, Vol. 83, No. 6, 04.06.2016, p. 365-373.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Fractal analysis of a new generation of HVOF sprayed coatings based on optical surface metrology
AU - Zou, Yibo
AU - Kästner, Markus
AU - Reithmeier, Eduard
PY - 2016/6/4
Y1 - 2016/6/4
N2 - In this article, fractal analysis combined with roughness measurement is proposed to characterize the new generations of HVOF sprayed coatings' surface textures. Two-dimensional and three-dimensional box counting algorithms are introduced to determine the fractal dimension, which is considered as a scale-invariant parameter and is able to describe chaos and complexity of the surface. For surface roughness metrology, a confocal laser scanning microscope with different lenses is used to acquire the areal topography, providing a sequence of height maps with different image resolutions. Typical areal roughness parameters are assessed based on the international standard ISO-25178. The results show that the fractal dimension is a powerful tool to depict the nature of the surface texture of the investigated coatings. Moreover, it is found that the traditional amplitude roughness parameters depend strongly on the range of the measurement field as well as the datasets' resolution, whereas the fractal dimension is rather invariant to the scales of the measured datasets. Finally, the correlation between the fractal dimension and roughness parameters is given at the end of this paper.
AB - In this article, fractal analysis combined with roughness measurement is proposed to characterize the new generations of HVOF sprayed coatings' surface textures. Two-dimensional and three-dimensional box counting algorithms are introduced to determine the fractal dimension, which is considered as a scale-invariant parameter and is able to describe chaos and complexity of the surface. For surface roughness metrology, a confocal laser scanning microscope with different lenses is used to acquire the areal topography, providing a sequence of height maps with different image resolutions. Typical areal roughness parameters are assessed based on the international standard ISO-25178. The results show that the fractal dimension is a powerful tool to depict the nature of the surface texture of the investigated coatings. Moreover, it is found that the traditional amplitude roughness parameters depend strongly on the range of the measurement field as well as the datasets' resolution, whereas the fractal dimension is rather invariant to the scales of the measured datasets. Finally, the correlation between the fractal dimension and roughness parameters is given at the end of this paper.
KW - box-count algorithm
KW - Fractal analysis
KW - new HVOF sprayed coating
KW - optical metrology
KW - roughness measurement
UR - http://www.scopus.com/inward/record.url?scp=84974705234&partnerID=8YFLogxK
U2 - 10.1515/teme-2016-0006
DO - 10.1515/teme-2016-0006
M3 - Article
AN - SCOPUS:84974705234
VL - 83
SP - 365
EP - 373
JO - Technisches Messen
JF - Technisches Messen
SN - 0171-8096
IS - 6
ER -