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A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry
The grinding grooves of material removal machining and the residues of a machining tool on the key component surface cause surface stress concentration. Thus, it is critical to carry out precise measurements on the key component surface to evaluate the stress concentration. Based on white-light inte...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575441/ https://www.ncbi.nlm.nih.gov/pubmed/37837137 http://dx.doi.org/10.3390/s23198307 |
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author | Chen, Junying Wang, Boxuan Chen, Xiuyu Jiang, Qingshan Feng, Wei Xu, Zhilong Zhao, Zhenye |
author_facet | Chen, Junying Wang, Boxuan Chen, Xiuyu Jiang, Qingshan Feng, Wei Xu, Zhilong Zhao, Zhenye |
author_sort | Chen, Junying |
collection | PubMed |
description | The grinding grooves of material removal machining and the residues of a machining tool on the key component surface cause surface stress concentration. Thus, it is critical to carry out precise measurements on the key component surface to evaluate the stress concentration. Based on white-light interferometry (WLI), we studied the measurement distortion caused by the reflected light from the steep side of the grinding groove being unable to return to the optical system for imaging. A threshold value was set to eliminate the distorted measurement points, and the cubic spline algorithm was used to interpolate the eliminated points for compensation. The compensation result agrees well with the atomic force microscope (AFM) measurement result. However, for residues on the surface, a practical method was established to obtain a microscopic 3D micro-topography point cloud and a super-depth-of-field fusion image simultaneously. Afterward, the semantic segmentation network U-net was adopted to identify the residues in the super-depth-of-field fusion image and achieved a recognition accuracy of 91.06% for residual identification. Residual feature information, including height, position, and size, was obtained by integrating the information from point clouds and super-depth-of-field fusion images. This work can provide foundational data to study surface stress concentration. |
format | Online Article Text |
id | pubmed-10575441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105754412023-10-14 A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry Chen, Junying Wang, Boxuan Chen, Xiuyu Jiang, Qingshan Feng, Wei Xu, Zhilong Zhao, Zhenye Sensors (Basel) Article The grinding grooves of material removal machining and the residues of a machining tool on the key component surface cause surface stress concentration. Thus, it is critical to carry out precise measurements on the key component surface to evaluate the stress concentration. Based on white-light interferometry (WLI), we studied the measurement distortion caused by the reflected light from the steep side of the grinding groove being unable to return to the optical system for imaging. A threshold value was set to eliminate the distorted measurement points, and the cubic spline algorithm was used to interpolate the eliminated points for compensation. The compensation result agrees well with the atomic force microscope (AFM) measurement result. However, for residues on the surface, a practical method was established to obtain a microscopic 3D micro-topography point cloud and a super-depth-of-field fusion image simultaneously. Afterward, the semantic segmentation network U-net was adopted to identify the residues in the super-depth-of-field fusion image and achieved a recognition accuracy of 91.06% for residual identification. Residual feature information, including height, position, and size, was obtained by integrating the information from point clouds and super-depth-of-field fusion images. This work can provide foundational data to study surface stress concentration. MDPI 2023-10-08 /pmc/articles/PMC10575441/ /pubmed/37837137 http://dx.doi.org/10.3390/s23198307 Text en © 2023 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 Chen, Junying Wang, Boxuan Chen, Xiuyu Jiang, Qingshan Feng, Wei Xu, Zhilong Zhao, Zhenye A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry |
title | A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry |
title_full | A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry |
title_fullStr | A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry |
title_full_unstemmed | A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry |
title_short | A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry |
title_sort | micro-topography measurement and compensation method for the key component surface based on white-light interferometry |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575441/ https://www.ncbi.nlm.nih.gov/pubmed/37837137 http://dx.doi.org/10.3390/s23198307 |
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