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A Novel Simulation Method of Micro-Topography for Grinding Surface
A novel simulation method of microtopography for grinding surface was proposed in this paper. Based on the theory of wavelet analysis, multiscale decomposition of the measured topography was conducted. The topography was divided into high frequency band (HFB), theoretical frequency band (TFB), and l...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470869/ https://www.ncbi.nlm.nih.gov/pubmed/34576352 http://dx.doi.org/10.3390/ma14185128 |
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author | An, Qi Suo, Shuangfu Bai, Yuzhu |
author_facet | An, Qi Suo, Shuangfu Bai, Yuzhu |
author_sort | An, Qi |
collection | PubMed |
description | A novel simulation method of microtopography for grinding surface was proposed in this paper. Based on the theory of wavelet analysis, multiscale decomposition of the measured topography was conducted. The topography was divided into high frequency band (HFB), theoretical frequency band (TFB), and low frequency band (LFB) by wavelet energy method. The high-frequency and the low-frequency topography were extracted to obtain the digital combination model. Combined with the digital combination model and the theoretical topography obtained by geometric simulation method, the simulation topography of grinding surface can be generated. Moreover, the roughness parameters of the measured topography and the simulation topography under different machining parameters were compared. The maximum relative error of Sa, Sq, Ssk and Sku were 1.79%, 2.24%, 4.69% and 4.73%, respectively, which verifies the feasibility and accuracy of the presented method. |
format | Online Article Text |
id | pubmed-8470869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84708692021-09-27 A Novel Simulation Method of Micro-Topography for Grinding Surface An, Qi Suo, Shuangfu Bai, Yuzhu Materials (Basel) Article A novel simulation method of microtopography for grinding surface was proposed in this paper. Based on the theory of wavelet analysis, multiscale decomposition of the measured topography was conducted. The topography was divided into high frequency band (HFB), theoretical frequency band (TFB), and low frequency band (LFB) by wavelet energy method. The high-frequency and the low-frequency topography were extracted to obtain the digital combination model. Combined with the digital combination model and the theoretical topography obtained by geometric simulation method, the simulation topography of grinding surface can be generated. Moreover, the roughness parameters of the measured topography and the simulation topography under different machining parameters were compared. The maximum relative error of Sa, Sq, Ssk and Sku were 1.79%, 2.24%, 4.69% and 4.73%, respectively, which verifies the feasibility and accuracy of the presented method. MDPI 2021-09-07 /pmc/articles/PMC8470869/ /pubmed/34576352 http://dx.doi.org/10.3390/ma14185128 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article An, Qi Suo, Shuangfu Bai, Yuzhu A Novel Simulation Method of Micro-Topography for Grinding Surface |
title | A Novel Simulation Method of Micro-Topography for Grinding Surface |
title_full | A Novel Simulation Method of Micro-Topography for Grinding Surface |
title_fullStr | A Novel Simulation Method of Micro-Topography for Grinding Surface |
title_full_unstemmed | A Novel Simulation Method of Micro-Topography for Grinding Surface |
title_short | A Novel Simulation Method of Micro-Topography for Grinding Surface |
title_sort | novel simulation method of micro-topography for grinding surface |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470869/ https://www.ncbi.nlm.nih.gov/pubmed/34576352 http://dx.doi.org/10.3390/ma14185128 |
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