Intelligent welding system technologies: State-of-the-art review and perspectives

Wang, Baicun; Hu, S. Jack; Sun, Lei; Freiheit, Theodor

doi:10.1016/j.jmsy.2020.06.020

Cited by 229 publications

(73 citation statements)

References 117 publications

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“…Ancient weapons made more than a thousand years ago can serve as the evidence of how old the welding technology is [ 1 ]. Nowadays, welding plays an outstanding role in industry and is used in such sectors as construction and building, transportation, energy, and others [ 2 , 3 ]. An important field in which welding technologies are widely used is the manufacturing and renovation of wear-resistant machine parts.…”

Section: Introductionmentioning

confidence: 99%

Microstructure and Properties of Heat Affected Zone in High-Carbon Steel after Welding with Fast Cooling in Water

et al. 2020

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The purpose of the research was to obtain an arc welded joint of a preliminary quenched high-carbon wear resistant steel without losing the structure that is previously obtained by heat treatment. 120Mn3Si2 steel was chosen for experiments due to its good resistance to mechanical wear. The fast cooling of welding joints in water was carried out right after welding. The major conclusion is that the soft austenitic layer appears in the vicinity of the fusion line as a result of the fast cooling of the welding joint. The microstructure of the heat affected zone of quenched 120Mn3Si2 steel after welding with rapid cooling in water consists of several subzones. The first one is a purely austenitic subzone, followed by austenite + martensite microstructure, and finally, an almost fully martensitic subzone. The rest of the heat affected zone is tempered material that is heated during welding below A1 critical temperature. ISO 4136 tensile tests were carried out for the welded joints of 120Mn3Si2 steel and 09Mn2Si low carbon steel (ASTM A516, DIN13Mn6 equivalent) after welding with fast cooling in water. The tests showed that welded joints are stronger than the quenched 120Mn3Si2 steel itself. The results of work can be used in industries where the severe mechanical wear of machine parts is a challenge.

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Section: Introductionmentioning

confidence: 99%

Microstructure and Properties of Heat Affected Zone in High-Carbon Steel after Welding with Fast Cooling in Water

et al. 2020

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“…In intelligent manufacturing, a weld controller is a typical system of the intelligent welding manufacturing system [1]. Intelligent control of welding dynamic process is one of main problems of intelligent welding technology.…”

Section: Introductionmentioning

confidence: 99%

Complex Behavior of Droplet Transfer and Spreading in Cold Metal Transfer

Yang

Xing

Yang

et al. 2020

Shock and Vibration

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In intelligent manufacturing, an intelligent control method of welding process is an important process of intelligent welding manufacturing technology (IWMT). Metal transfer is a key factor to control the welding process. Metal transfer and droplet spreading are of vital importance for welding formation. A new theoretical model of cold metal transfer (CMT) in short-circuit transfer mode is proposed in this paper. In this model, the CMT welding process is regarded as a continuous process of arc heating, mass transfer, short-circuit, and spreading, and the relations between these processes are analyzed. The calculation equations used by the model can analyze the welding formation clearly and simplify the complex welding process into continuous physical behavior. The predicted welding width shows good agreement with the measurement results. The mechanism of increased welding width is also comprehensively analyzed. Results have a certain guiding effect on aluminum alloy welding process control.

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“…Laser welding is a complicated manufacturing process with high energy density and high efficiency, while humans have limited understanding of the process mechanism [ 1 , 2 ]. The welding quality can be influenced by various factors such as the internal defects of materials and the complex manufacturing environment.…”

Section: Introductionmentioning

confidence: 99%

Multi-Output Monitoring of High-Speed Laser Welding State Based on Deep Learning

Xue

Chang

2021

Sensors

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In order to ensure the production quality of high-speed laser welding, it is necessary to simultaneously monitor multiple state properties. Monitoring methods combining vision sensing and deep learning models are popular but most models used can only make predictions on single welding state property. In this contribution, we propose a multi-output model based on a lightweight convolutional neural network (CNN) architecture and introduce the particle swarm optimization (PSO) technique to optimize the loss function of the model, to simultaneously monitor multiple state properties of high-speed laser welding of AISI 304 austenitic stainless steel. High-speed imaging is performed to capture images of the melt pool and the dataset is built. Test results of different models show that the proposed model can achieve monitoring of multiple welding state properties accurately and efficiently. In addition, we make an interpretation and discussion on the prediction of the model through a visualization method, which can help to deepen our understanding of the relationship between the melt pool appearance and welding state. The proposed method can not only be applied to the monitoring of high-speed laser welding but also has the potential to be used in other procedures of welding state monitoring.

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Intelligent welding system technologies: State-of-the-art review and perspectives

Cited by 229 publications

References 117 publications

Microstructure and Properties of Heat Affected Zone in High-Carbon Steel after Welding with Fast Cooling in Water

Microstructure and Properties of Heat Affected Zone in High-Carbon Steel after Welding with Fast Cooling in Water

Complex Behavior of Droplet Transfer and Spreading in Cold Metal Transfer

Multi-Output Monitoring of High-Speed Laser Welding State Based on Deep Learning

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