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Multiscale characterization and contact performance analysis of machining surfaces
Accurately characterizing the surface topography of parts is crucial to improve the surface measurement accuracy and analyze the surface contact performance. A method is proposed to separate the morphological characteristics of the actual machined surface based on the layer-by-layer error reconstruc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272123/ https://www.ncbi.nlm.nih.gov/pubmed/37322105 http://dx.doi.org/10.1038/s41598-023-36907-6 |
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author | Li, Ling Zhang, Wang Wang, Jingjing Ruan, Xiaoguang Li, Lixia Xie, Miaoxia |
author_facet | Li, Ling Zhang, Wang Wang, Jingjing Ruan, Xiaoguang Li, Lixia Xie, Miaoxia |
author_sort | Li, Ling |
collection | PubMed |
description | Accurately characterizing the surface topography of parts is crucial to improve the surface measurement accuracy and analyze the surface contact performance. A method is proposed to separate the morphological characteristics of the actual machined surface based on the layer-by-layer error reconstruction method and the signal-to-noise ratio method during the wavelet transform process, so as to evaluate the contact performance of the different joint surfaces. First, the actual machined surface morphological features are separated by using the wavelet transform method, the layer-by-layer error reconstruction method, and the signal-to-noise ratio method. Second, the reconstructed three-dimensional surface contact model is established by the reverse modeling engineering method. Third, the finite element method is used to analyze the impact of processing methods and surface roughness on contact surface parameters. The result demonstrates that the simplified and efficient three-dimensional reconstructed surface is achieved based on the real machining surface in contrast to other existing approaches. The surface roughness has a more significant influence on contact performance. The contact deformation increases with the increase of surface roughness, while the curves of average contact stress, contact stiffness, and contact area have the opposite trend. |
format | Online Article Text |
id | pubmed-10272123 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102721232023-06-17 Multiscale characterization and contact performance analysis of machining surfaces Li, Ling Zhang, Wang Wang, Jingjing Ruan, Xiaoguang Li, Lixia Xie, Miaoxia Sci Rep Article Accurately characterizing the surface topography of parts is crucial to improve the surface measurement accuracy and analyze the surface contact performance. A method is proposed to separate the morphological characteristics of the actual machined surface based on the layer-by-layer error reconstruction method and the signal-to-noise ratio method during the wavelet transform process, so as to evaluate the contact performance of the different joint surfaces. First, the actual machined surface morphological features are separated by using the wavelet transform method, the layer-by-layer error reconstruction method, and the signal-to-noise ratio method. Second, the reconstructed three-dimensional surface contact model is established by the reverse modeling engineering method. Third, the finite element method is used to analyze the impact of processing methods and surface roughness on contact surface parameters. The result demonstrates that the simplified and efficient three-dimensional reconstructed surface is achieved based on the real machining surface in contrast to other existing approaches. The surface roughness has a more significant influence on contact performance. The contact deformation increases with the increase of surface roughness, while the curves of average contact stress, contact stiffness, and contact area have the opposite trend. Nature Publishing Group UK 2023-06-15 /pmc/articles/PMC10272123/ /pubmed/37322105 http://dx.doi.org/10.1038/s41598-023-36907-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Li, Ling Zhang, Wang Wang, Jingjing Ruan, Xiaoguang Li, Lixia Xie, Miaoxia Multiscale characterization and contact performance analysis of machining surfaces |
title | Multiscale characterization and contact performance analysis of machining surfaces |
title_full | Multiscale characterization and contact performance analysis of machining surfaces |
title_fullStr | Multiscale characterization and contact performance analysis of machining surfaces |
title_full_unstemmed | Multiscale characterization and contact performance analysis of machining surfaces |
title_short | Multiscale characterization and contact performance analysis of machining surfaces |
title_sort | multiscale characterization and contact performance analysis of machining surfaces |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272123/ https://www.ncbi.nlm.nih.gov/pubmed/37322105 http://dx.doi.org/10.1038/s41598-023-36907-6 |
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