Journal ArticleDOI
Modeling of pulsed GTAW based on multi‐sensor fusion
Bo Chen,Jifeng Wang,Shanben Chen +2 more
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TLDR
Wang et al. as discussed by the authors used different sensors to get different information about the welding process, and uses multi-sensor information fusion technology to fuse the different information to predict the backside width of weld pool.Abstract:
Purpose – Welding process is a complicated process influenced by many interference factors, a single sensor cannot get information describing welding process roundly. This paper simultaneously uses different sensors to get different information about the welding process, and uses multi‐sensor information fusion technology to fuse the different information. By using multi‐sensors, this paper aims to describe the welding process more precisely.Design/methodology/approach – Electronic and welding pool image information are, respectively, obtained by arc sensor and image sensor, then electronic signal processing and image processing algorithms are used to extract the features of the signals, the features are then fused by neural network to predict the backside width of weld pool.Findings – Comparative experiments show that the multi‐sensor fusion technology can predict the weld pool backside width more precisely.Originality/value – The multi‐sensor fusion technology is used to fuse the different information o...read more
Citations
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Journal ArticleDOI
Fabrication of iron-rich Fe–Al intermetallics using the wire-arc additive manufacturing process
TL;DR: In this article, a wire-arc additive manufacturing (WAAM) system is used to fabricate iron rich Fe-Al intermetallics with 25% aluminum content, which is produced in situ through controlled addition of the elemental iron and aluminum components into the welding process and assessed using optical microstructure analysis, hardness testing, tensile testing, X-ray diffraction phase characterization and electron dispersive spectrometry.
Journal ArticleDOI
Application of sensing techniques and artificial intelligence-based methods to laser welding real-time monitoring: A critical review of recent literature
TL;DR: This fundamental work aims to review the research progress in laser welding monitoring and provide a basis for follow-on research on the potential research problems and challenges based on real-time intelligent monitoring.
Journal ArticleDOI
Detecting dynamic development of weld pool using machine learning from innovative composite images for adaptive welding
Yongchao Cheng,Yongchao Cheng,Qiyue Wang,Wenhua Jiao,Rui Yu,Shujun Chen,YuMing Zhang,Jun Xiao +7 more
TL;DR: In this paper, a convolutional neural network (CNN) was used to identify the penetration states of the weld pool surface and the generated training model is used to reduce the welding current to the base level after the desired penetration state.
Journal ArticleDOI
Audio sensing and modeling of arc dynamic characteristic during pulsed Al alloy GTAW process
TL;DR: In this article, the relationship between arc sound signal and arc height through arc sound features of GTAW welding was investigated. But the authors focused on detecting different arc height by using ANNs.
Journal ArticleDOI
Research on detection of welding penetration state during robotic GTAW process based on audible arc sound
TL;DR: The experiment results demonstrated that each feature in time and frequency domain could react the penetration behaviour, arc sound in different frequency band had different performance at different penetration states and the prediction model established by 23 features in time domain and frequencydomain got the best prediction effect to recognize different penetration state and welding quality through arc sound signal.
References
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