This preprint is under consideration at Chinese Journal of Mechanical Engineering. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
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Original Article
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 CC BY 4.0 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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CURRENT STATUS: Under Review
Version 1
Posted 19 May, 2020
No community comments so far
Editorial decision: Minor revision
On 28 Dec, 2020
Review #1 received
Received 23 Jun, 2020
Review #2 received
Received 23 Jun, 2020
Reviewer #1 agreed
On 02 Jun, 2020
Reviewer #2 agreed
On 02 Jun, 2020
Reviewers invited
Invitations sent on 01 Jun, 2020
First submitted
On 12 May, 2020
Editor assigned
On 12 May, 2020
Submission checks complete
On 11 May, 2020
Editor invited
On 11 May, 2020
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Subject Areas
Structural Biology
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This preprint is under consideration at Chinese Journal of Mechanical Engineering. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Original Article
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
Editorial decision: Minor revision
On 28 Dec, 2020
Review #1 received
Received 23 Jun, 2020
Review #2 received
Received 23 Jun, 2020
Reviewer #1 agreed
On 02 Jun, 2020
Reviewer #2 agreed
On 02 Jun, 2020
Reviewers invited
Invitations sent on 01 Jun, 2020
First submitted
On 12 May, 2020
Editor assigned
On 12 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 CC BY 4.0 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
This preprint is available for download as a PDF.
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