Original Outline: d_fine.
<div><p>Surface roughness is a critical parameter used to describe the microscopic geometric deviations of a part, and serves as an essential indicator for assessing the quality of surface processing in various mechanical components. This study evaluates Singular Spectrum Analysis (SSA)...
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2025
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| _version_ | 1849927629141966848 |
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| author | Ziming Pang (22683291) |
| author2 | Xiaochuan Gan (22683294) Ming Kong (1836898) |
| author2_role | author author |
| author_facet | Ziming Pang (22683291) Xiaochuan Gan (22683294) Ming Kong (1836898) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ziming Pang (22683291) Xiaochuan Gan (22683294) Ming Kong (1836898) |
| dc.date.none.fl_str_mv | 2025-11-25T18:25:41Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0336936.g001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Original_Outline_d_fine_/30713481 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biochemistry Medicine Microbiology Cell Biology Sociology Immunology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified various mechanical components microscopic geometric deviations critical parameter used assessed profile (< arithmetical mean deviation div >< p findings establish ssa findings indicate window length viable alternative surface roughness surface processing study investigates ssa ’ ssa technique rq </ rku </ ra </ obtained using gaussian filter essential indicator broad applications |
| dc.title.none.fl_str_mv | Original Outline: d_fine. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <div><p>Surface roughness is a critical parameter used to describe the microscopic geometric deviations of a part, and serves as an essential indicator for assessing the quality of surface processing in various mechanical components. This study evaluates Singular Spectrum Analysis (SSA) for surface roughness profile separation, comparing its effectiveness with the ISO standard Gaussian filter. Using NIST roughness measurement data, this study investigates how SSA’s window length and grouping method affect roughness parameters. The findings indicate that with an appropriately chosen window length, the SSA technique can effectively separate roughness signals and yield roughness parameter values comparable to those obtained using the Gaussian filter, such as the arithmetical mean deviation of the assessed profile (<i>Ra</i>), the root mean square deviation of the assessed profile (<i>Rq</i>), and the kurtosis of the assessed profile (<i>Rku</i>). These findings establish SSA as a viable alternative for surface roughness profile separation, with broad applications in surface metrology.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_883c218505919cfa67dc49a92fa305cf |
| identifier_str_mv | 10.1371/journal.pone.0336936.g001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30713481 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Original Outline: d_fine.Ziming Pang (22683291)Xiaochuan Gan (22683294)Ming Kong (1836898)BiochemistryMedicineMicrobiologyCell BiologySociologyImmunologyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedChemical Sciences not elsewhere classifiedvarious mechanical componentsmicroscopic geometric deviationscritical parameter usedassessed profile (<arithmetical mean deviationdiv >< pfindings establish ssafindings indicatewindow lengthviable alternativesurface roughnesssurface processingstudy investigatesssa ’ssa techniquerq </rku </ra </obtained usinggaussian filteressential indicatorbroad applications<div><p>Surface roughness is a critical parameter used to describe the microscopic geometric deviations of a part, and serves as an essential indicator for assessing the quality of surface processing in various mechanical components. This study evaluates Singular Spectrum Analysis (SSA) for surface roughness profile separation, comparing its effectiveness with the ISO standard Gaussian filter. Using NIST roughness measurement data, this study investigates how SSA’s window length and grouping method affect roughness parameters. The findings indicate that with an appropriately chosen window length, the SSA technique can effectively separate roughness signals and yield roughness parameter values comparable to those obtained using the Gaussian filter, such as the arithmetical mean deviation of the assessed profile (<i>Ra</i>), the root mean square deviation of the assessed profile (<i>Rq</i>), and the kurtosis of the assessed profile (<i>Rku</i>). These findings establish SSA as a viable alternative for surface roughness profile separation, with broad applications in surface metrology.</p></div>2025-11-25T18:25:41ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0336936.g001https://figshare.com/articles/figure/Original_Outline_d_fine_/30713481CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307134812025-11-25T18:25:41Z |
| spellingShingle | Original Outline: d_fine. Ziming Pang (22683291) Biochemistry Medicine Microbiology Cell Biology Sociology Immunology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified various mechanical components microscopic geometric deviations critical parameter used assessed profile (< arithmetical mean deviation div >< p findings establish ssa findings indicate window length viable alternative surface roughness surface processing study investigates ssa ’ ssa technique rq </ rku </ ra </ obtained using gaussian filter essential indicator broad applications |
| status_str | publishedVersion |
| title | Original Outline: d_fine. |
| title_full | Original Outline: d_fine. |
| title_fullStr | Original Outline: d_fine. |
| title_full_unstemmed | Original Outline: d_fine. |
| title_short | Original Outline: d_fine. |
| title_sort | Original Outline: d_fine. |
| topic | Biochemistry Medicine Microbiology Cell Biology Sociology Immunology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified various mechanical components microscopic geometric deviations critical parameter used assessed profile (< arithmetical mean deviation div >< p findings establish ssa findings indicate window length viable alternative surface roughness surface processing study investigates ssa ’ ssa technique rq </ rku </ ra </ obtained using gaussian filter essential indicator broad applications |