This preprint is under consideration at Chinese Journal of Mechanical Engineering. Preprints are preliminary reports that have not undergone peer review. They should not be considered conclusive, used to inform clinical practice, or referenced by the media as validated information.
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Original Article
A Comparative Study on Asperity Peak Modeling Methods
Wei Zhou
Hunan University of Science and Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5503-6834
License:
This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
The peak identification scheme based method (three-point definition) and the spectral moments based method (spectral moment approach) are both widely used for asperity peak modeling in tribology. To discover the differences between the two methods, a great number of rough surface profile samples with various statistical distributions are first randomly generated using FFT. Then the distribution parameters of asperity peaks are calculated for the generated samples with both methods. The obtained results are compared and verified by experiment. The variation rules of the differences between the two methods with statistical characteristics of rough surfaces are investigated. To explain for the discovered differences, the assumptions by spectral moment approach that the joint distribution of surface height, slope and curvature is normal and that the height distribution of asperities is Gaussian, are examined. The results show that it is unreasonable to assume a joint normal distribution without inspecting the correlation pattern of [z], [z′] and [z′′], and that the height distribution of asperities is not exactly Gaussian before correlation length of rough surface increases to a certain extent, 20 for instance.
Keywords
Surface topography, Roughness , Surface analysis , Asperity peak , Random process model
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This preprint is under consideration at Chinese Journal of Mechanical Engineering. Preprints are preliminary reports that have not undergone peer review. They should not be considered conclusive, used to inform clinical practice, or referenced by the media as validated information.
Learn more about In Review
Original Article
A Comparative Study on Asperity Peak Modeling Methods
Wei Zhou
Hunan University of Science and Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5503-6834
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 19 May, 2020
No community comments so far
First submitted
On 11 May, 2020
Editor assigned
On 11 May, 2020
Submission checks complete
On 11 May, 2020
Editor invited
On 11 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Structural Biology
License:
This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
The peak identification scheme based method (three-point definition) and the spectral moments based method (spectral moment approach) are both widely used for asperity peak modeling in tribology. To discover the differences between the two methods, a great number of rough surface profile samples with various statistical distributions are first randomly generated using FFT. Then the distribution parameters of asperity peaks are calculated for the generated samples with both methods. The obtained results are compared and verified by experiment. The variation rules of the differences between the two methods with statistical characteristics of rough surfaces are investigated. To explain for the discovered differences, the assumptions by spectral moment approach that the joint distribution of surface height, slope and curvature is normal and that the height distribution of asperities is Gaussian, are examined. The results show that it is unreasonable to assume a joint normal distribution without inspecting the correlation pattern of [z], [z′] and [z′′], and that the height distribution of asperities is not exactly Gaussian before correlation length of rough surface increases to a certain extent, 20 for instance.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.