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Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling
In this study, the burr and slot widths formed after the micro-milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user-defined subroutine for image processing. To determine the accuracy of the developed im...
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/PMC8271581/ https://www.ncbi.nlm.nih.gov/pubmed/34203468 http://dx.doi.org/10.3390/s21134432 |
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author | Akkoyun, Fatih Ercetin, Ali Aslantas, Kubilay Pimenov, Danil Yurievich Giasin, Khaled Lakshmikanthan, Avinash Aamir, Muhammad |
author_facet | Akkoyun, Fatih Ercetin, Ali Aslantas, Kubilay Pimenov, Danil Yurievich Giasin, Khaled Lakshmikanthan, Avinash Aamir, Muhammad |
author_sort | Akkoyun, Fatih |
collection | PubMed |
description | In this study, the burr and slot widths formed after the micro-milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user-defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured using a scanning electron microscope (SEM). The captured images were processed with computer vision software, which was written in C++ programming language and open-sourced computer library (Open CV). According to the results, it was determined that there is a good correlation between automated and manual measurements of slot and burr widths. The accuracy of the proposed method is above 91%, 98%, and 99% for up milling, down milling, and slot measurements, respectively. The conducted study offers a user-friendly, fast, and accurate solution using computer vision (CV) technology by requiring only one SEM image as input to characterize slot and burr formation. |
format | Online Article Text |
id | pubmed-8271581 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82715812021-07-11 Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling Akkoyun, Fatih Ercetin, Ali Aslantas, Kubilay Pimenov, Danil Yurievich Giasin, Khaled Lakshmikanthan, Avinash Aamir, Muhammad Sensors (Basel) Article In this study, the burr and slot widths formed after the micro-milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user-defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured using a scanning electron microscope (SEM). The captured images were processed with computer vision software, which was written in C++ programming language and open-sourced computer library (Open CV). According to the results, it was determined that there is a good correlation between automated and manual measurements of slot and burr widths. The accuracy of the proposed method is above 91%, 98%, and 99% for up milling, down milling, and slot measurements, respectively. The conducted study offers a user-friendly, fast, and accurate solution using computer vision (CV) technology by requiring only one SEM image as input to characterize slot and burr formation. MDPI 2021-06-28 /pmc/articles/PMC8271581/ /pubmed/34203468 http://dx.doi.org/10.3390/s21134432 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 Akkoyun, Fatih Ercetin, Ali Aslantas, Kubilay Pimenov, Danil Yurievich Giasin, Khaled Lakshmikanthan, Avinash Aamir, Muhammad Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling |
title | Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling |
title_full | Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling |
title_fullStr | Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling |
title_full_unstemmed | Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling |
title_short | Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling |
title_sort | measurement of micro burr and slot widths through image processing: comparison of manual and automated measurements in micro-milling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271581/ https://www.ncbi.nlm.nih.gov/pubmed/34203468 http://dx.doi.org/10.3390/s21134432 |
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