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Noncontact Ultrasonic Sensing of Weld Pools for Automated Welding
1989Contacting ultrasonic techniques can determine the geometry of the molten/solid interface [1,2] and detect conditions which could lead to defect formation [3]. However, the couplant required is a potential source of contamination in the weld and may be difficult to use under industrial conditions.
John A. Johnson, Nancy M. Carlson
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A novel control algorithm for weld pool control
Industrial Robot: An International Journal, 2010PurposeQuality control of arc welding process is the key component in robotic welding system. The purpose of this paper is to address vision‐sensing technology and model‐free adaptive control (MFC) of weld pool size during automatic arc welding system.Design/methodology/approachThe shape and size parameters for the weld pool are used to describe the ...
Fenglin Lü +3 more
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Dynamic evolution of the weld pool reflection during weld penetration development
2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), 2016Weld pool surface is believed to contain sufficient information to determine the weld penetration from which skilled welders are able to control the welding process to desired penetration states. However, it is unclear how human welders extract the weld penetration from the observed weld pool surface.
Jinsong Chen +3 more
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Adaptive modeling of the weld pool geometry in gas tungsten arc welding
2013 10th IEEE INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC), 2013Skilled welders can observe the weld pool and control the welding process accordingly. This implies that an advanced control system could be developed to control the welding process by emulating the estimation and decision making process of the human welder.
YuKang Liu, Yuming Zhang
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A device for removing metal from the weld pool when studying the shape of the weld pool
Welding International, 2017A.G. Grigoryants +3 more
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Influencing the Weld Pool During Laser Welding
2018S. Nothdurft, A. Springer, S. Kaierle
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Weld Pool Dynamics in Deep Penetration Laser Welding
2021Shuili Gong +3 more
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Machine learning of weld joint penetration from weld pool surface using support vector regression
Journal of Manufacturing Processes, 2019Yuming Zhang, Yu Luo, Rui Yu
exaly