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Shanben Chen
Researcher at Shanghai Jiao Tong University
Publications - 66
Citations - 2093
Shanben Chen is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Welding & Robot welding. The author has an hindex of 25, co-authored 65 publications receiving 1555 citations. Previous affiliations of Shanben Chen include Harbin Institute of Technology.
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Real-time seam tracking control technology during welding robot GTAW process based on passive vision sensor
TL;DR: In this article, a real-time seam tracking method was proposed to overcome the deficiencies of teaching-playback welding robots in seam tracking during gas tungsten arc welding (GTAW) process.
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Weld image deep learning-based on-line defects detection using convolutional neural networks for Al alloy in robotic arc welding
TL;DR: Wang et al. as discussed by the authors proposed a deep learning-based on-line defect detection for aluminum alloy in robotic arc welding using convolutional neural networks (CNN) and weld images.
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Computer vision technology for seam tracking in robotic GTAW and GMAW
TL;DR: A set of special vision system has been designed firstly, which can acquire clear and steady real-time weld images and secondly, a new and improved edge detection algorithm was proposed to detect the edges in weld images, and more accurately extract the seam and pool characteristic parameters.
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Research evolution on intelligentized technologies for arc welding process
Shanben Chen,Na Lv +1 more
TL;DR: In this article, the authors present some new evolutions of research works in the IRWTL at SJTU on intelligentized technologies for arc welding dynamic process and robot systems, including multi-information sensing of arc welding process, such as characteristic extraction of weld pool image, voltage, current, and sound, arc-spectral features.
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Visual sensing and penetration control in aluminum alloy pulsed GTA welding .
TL;DR: In this article, a three-optical-route visual sensor was designed to capture the weld pool from three directions at the same time, and serials of clear and stable weld pool images were obtained.