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Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System
Arc length is a crucial parameter of the manual metal arc (MMA) welding process, as it influences the arc voltage and the resulting welded joint. In the MMA method, the process’ stability is mainly controlled by the skills of a welder. According to that, giving the feedback about the arc length as w...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796377/ https://www.ncbi.nlm.nih.gov/pubmed/33375601 http://dx.doi.org/10.3390/s21010084 |
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author | Jamrozik, Wojciech Górka, Jacek |
author_facet | Jamrozik, Wojciech Górka, Jacek |
author_sort | Jamrozik, Wojciech |
collection | PubMed |
description | Arc length is a crucial parameter of the manual metal arc (MMA) welding process, as it influences the arc voltage and the resulting welded joint. In the MMA method, the process’ stability is mainly controlled by the skills of a welder. According to that, giving the feedback about the arc length as well as the welding speed to the welder is a valuable property at the stage of weld training and in the production of welded elements. The proposed solution is based on the application of relatively cheap Complementary Metal Oxide Semiconductor (CMOS) cameras to track the welding electrode tip and to estimate the geometrical properties of welding arc. All measured parameters are varying during welding. To validate the results of image processing, arc voltage was measured as a reference value describing in some part the process stability. |
format | Online Article Text |
id | pubmed-7796377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77963772021-01-10 Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System Jamrozik, Wojciech Górka, Jacek Sensors (Basel) Article Arc length is a crucial parameter of the manual metal arc (MMA) welding process, as it influences the arc voltage and the resulting welded joint. In the MMA method, the process’ stability is mainly controlled by the skills of a welder. According to that, giving the feedback about the arc length as well as the welding speed to the welder is a valuable property at the stage of weld training and in the production of welded elements. The proposed solution is based on the application of relatively cheap Complementary Metal Oxide Semiconductor (CMOS) cameras to track the welding electrode tip and to estimate the geometrical properties of welding arc. All measured parameters are varying during welding. To validate the results of image processing, arc voltage was measured as a reference value describing in some part the process stability. MDPI 2020-12-25 /pmc/articles/PMC7796377/ /pubmed/33375601 http://dx.doi.org/10.3390/s21010084 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jamrozik, Wojciech Górka, Jacek Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System |
title | Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System |
title_full | Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System |
title_fullStr | Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System |
title_full_unstemmed | Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System |
title_short | Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System |
title_sort | assessing mma welding process stability using machine vision-based arc features tracking system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796377/ https://www.ncbi.nlm.nih.gov/pubmed/33375601 http://dx.doi.org/10.3390/s21010084 |
work_keys_str_mv | AT jamrozikwojciech assessingmmaweldingprocessstabilityusingmachinevisionbasedarcfeaturestrackingsystem AT gorkajacek assessingmmaweldingprocessstabilityusingmachinevisionbasedarcfeaturestrackingsystem |