Deep learning-based welding image recognition: A comprehensive review

T Liu, P Zheng, J Bao - Journal of Manufacturing Systems, 2023 - Elsevier
The reliability and accuracy of welding image recognition (WIR) is critical, which can largely
improve domain experts' insight of the welding system. To ensure its performance, deep …

Review on the solid-state welding of steels: diffusion bonding and friction stir welding processes

M Khedr, A Hamada, A Järvenpää, S Elkatatny… - Metals, 2022 - mdpi.com
Solid-state welding (SSW) is a relatively new technique, and ongoing research is being
performed to fulfill new design demands, deal with contemporary material advancements …

Measurement of pulsed laser welding penetration based on keyhole dynamics and deep learning approach

S Liu, D Wu, Z Luo, P Zhang, X Ye, Z Yu - Measurement, 2022 - Elsevier
The keyhole instability is a key concern in laser deep-penetration welding of high reflectivity
materials, potentially impacting the penetration status and weld quality. Monitoring and …

Review on multi-information acquisition, defect prediction and quality control of aluminum alloy GTAW process

Y Xu, Q Liu, J Xu, R Xiao, S Chen - Journal of Manufacturing Processes, 2023 - Elsevier
The gas tungsten arc welding (GTAW) is a classic traditional welding method for aluminum
alloys. However, the strong reflection of the welding area illuminated by arc light and the …

An attention-based bilinear feature extraction mechanism for fine-grained laser welding molten pool/keyhole defect recognition

T Liu, P Zheng, H Chen, L Zhang - Journal of Manufacturing Processes, 2023 - Elsevier
Vision-based molten pool/keyhole (MPK) defect recognition is essential for online
monitoring of laser welding quality. However, the visual differences corresponding to …

Improved convolutional neural network for laser welding defect prediction

W Huang, X Gao, Y Huang, Y Zhang - International Journal of Precision …, 2023 - Springer
In order to predict the laser welding defects, a convolutional neural network prediction model
is established. The keyhole image and plume image collected by a high-speed camera are …

[HTML][HTML] Advancements in control systems and integration of artificial intelligence in welding robots: A review

JT Kahnamouei, M Moallem - Ocean Engineering, 2024 - Elsevier
Welding automation has witnessed significant advancements with the integration of control
systems and artificial intelligence (AI) in welding robots. This review paper explores the …

Machine learning-based in-process monitoring for laser deep penetration welding: A survey

R Lu, M Lou, Y Xia, S Huang, Z Li, T Lyu, Y Wu… - … Applications of Artificial …, 2024 - Elsevier
In-process monitoring (IPM) of laser deep penetration welding (LDPW) has witnessed a
rapid growth in approaches that embrace machine learning algorithms, utilizing raw sensor …

Progress and perspectives of joints defects of laser-arc hybrid welding: A review

Q Liu, D Wu, Q Wang, P Zhang, H Yan, T Sun… - The International Journal …, 2024 - Springer
Laser-arc hybrid welding (LAHW), being a high-efficiency with excellent properties of high
welding speed, deep penetration, and good bridging performance, has been paid close …

Prediction of electron beam weld quality from weld bead surface using clustering and support vector regression

S Jaypuria, V Bondada, SK Gupta, DK Pratihar… - Expert Systems with …, 2023 - Elsevier
Destructive manual experiments are primarily used for quality assessment of electron beam
welded components, which consume the resources and time significantly. Vision-based and …