Characterization of “Humping” in the GTA welding process using infrared images

Variable polarity cold metal transfer (VPCMT) is a newly developed welding process and has drawn extensive interests because of its potential in further reducing the heat input, offering greater gap bridging ability, and improving the deposition rate. Using 6061 aluminum alloy as an example, this paper systematically investigated the influences of the key parameter in VPCMT, i.e., "positive/negative electrodes ratio (EP/EN Balance)," on weld formation, microstructure, and mechanical properties. It was found that, with the increase of the EP/EN Balance value, the duty cycle of the negative phase was reduced but the peak current and maximum temperature of the weld pool were both increased resulting in a higher heat input. The positive/negative electrode ratio had little impact on the grain misorientation angle in the fusion zone. Hardness of the joint was higher with larger positive duty cycles because of the precipitate phase and small grain size. An increased negative duty cycle resulted in lower heat input leading to insufficient melting of the material and deterioration of the mechanical strength of the welds.

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“…The formula governing the intensity of emitted radiation according to the absolute temperature was known as Planck's law [13]:…”

Section: Effect On Infrared Imagingmentioning

confidence: 99%

Effect of positive/negative electrode ratio on cold metal transfer welding of 6061 aluminum alloy

Zhang

Yan

et al. 2019

Int J Adv Manuf Technol

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“…Several works detect online the most common defects with the analysis of differences in spatial and temporal temperature distributions and use the Kalman filter, cumulative sum-among other methods-or combined with other information. Some examples can be found in [35,36,69,78,88,93,96,97,101,103,105,124]. Figure 13 shows the obvious differences between waveforms in a stable process and when there are discontinuities or a lack of penetration.…”

Section: Estimation Of the Weld Bead Depthmentioning

confidence: 99%

“…The pool surface emissivity oscillates with the temperature, surface finish and material type. The weld pool in the liquid phase has a surface almost like a mirror, which results in a low emissivity [103].…”

Section: Estimation Of the Weld Bead Depthmentioning

confidence: 99%

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Bestard

Alfaro

2018

J Braz. Soc. Mech. Sci. Eng.

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The arc welding process is widely used in industry, but the automatic control is limited by the difficulty in the process for measuring the principal magnitudes and to close the control loop. Adverse environmental conditions make use of conventional measurement systems difficult for obtaining information of the weld bead geometry. Under these conditions, indirect sensing techniques are a good option. Different sensing and estimation techniques are used, but few researchers are focusing on the flat welding position. The theory and practice prove that the dynamic models are the best representation to control the welding process, but most studies are performed with static models. This work is a review of the algorithms and sensing techniques used for collecting values of the arc welding process that allow the measurement or estimation of the weld bead geometry. Special attention is given to sensor fusion techniques due to its promising future in the welding process. Discussed in this text are the papers, patents, thesis and other documents found on the theme. It shows a summary of their evolution over the last 50 years.

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“…The main limiting factor regarding manufacturing productivity is the incidence of weld defects, usually at high currents and welding speeds [3]. Besides, a sub-optimal utilization of welding machines implies expensive losses in production, e.g.…”

Section: Introductionmentioning

confidence: 99%

Embedded vision system for monitoring arc welding with thermal imaging and deep learning

Fernandez

Souto

González

et al. 2020

2020 International Conference on Omni-Layer Intelligent Systems (COINS)

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We develop a novel embedded vision system for online monitoring of arc welding with thermal imaging. The thermal images are able to provide clear information of the melt pool and surrounding areas during the welding process. We propose a deep learning processing pipeline with a CNN-LSTM architecture for the detection and classification of defects based on video sequences. The experimental results show that the CNN-LSTM architecture is able to model the complex dynamics of the welding process and detect and classify defects with high accuracy. In addition, the embedded vision system implements an OPC-UA server, enabling an easy vertical and horizontal integration in Industry 4.0.

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Characterization of “Humping” in the GTA welding process using infrared images

Cited by 38 publications

References 10 publications

Effect of positive/negative electrode ratio on cold metal transfer welding of 6061 aluminum alloy

Effect of positive/negative electrode ratio on cold metal transfer welding of 6061 aluminum alloy

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Embedded vision system for monitoring arc welding with thermal imaging and deep learning

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