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Article

Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System

1
Department of Fundamentals of Machinery Design, Silesian University of Technology, 44-100 Gliwice, Poland
2
Department of Welding Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(1), 84; https://doi.org/10.3390/s21010084
Received: 14 December 2020 / Revised: 20 December 2020 / Accepted: 22 December 2020 / Published: 25 December 2020
(This article belongs to the Special Issue Sensor Fusion for Object Detection, Classification and Tracking)
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. View Full-Text
Keywords: MMA welding; welding arc; vision system; process monitoring; welding arc stability MMA welding; welding arc; vision system; process monitoring; welding arc stability
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MDPI and ACS Style

Jamrozik, W.; Górka, J. Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System. Sensors 2021, 21, 84. https://doi.org/10.3390/s21010084

AMA Style

Jamrozik W, Górka J. Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System. Sensors. 2021; 21(1):84. https://doi.org/10.3390/s21010084

Chicago/Turabian Style

Jamrozik, Wojciech, and Jacek Górka. 2021. "Assessing MMA Welding Process Stability Using Machine Vision-Based Arc Features Tracking System" Sensors 21, no. 1: 84. https://doi.org/10.3390/s21010084

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