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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...

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Detalles Bibliográficos
Autores principales: Jamrozik, Wojciech, Górka, Jacek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
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.
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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
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