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Record Nr. |
UNINA9910483951203321 |
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Autore |
Chen Zongyao |
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Titolo |
Key Technologies of Intelligentized Welding Manufacturing : Visual Sensing of Weld Pool Dynamic Characters and Defect Prediction of GTAW Process / / by Zongyao Chen, Zhili Feng, Jian Chen |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021 |
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ISBN |
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Edizione |
[1st ed. 2021.] |
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Descrizione fisica |
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1 online resource (103 pages) : illustrations |
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Disciplina |
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Soggetti |
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Robotics |
Automation |
Machine learning |
Manufactures |
Control engineering |
Robotics and Automation |
Machine Learning |
Manufacturing, Machines, Tools, Processes |
Control and Systems Theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Monitoring of Weld Pool Surface with Active Vision -- Visual Sensing of 3D Weld Pool Geometry with Passive Vision -- Penetration prediction with data driven models -- Penetration Control for Bead-on plate weld -- Penetration Detection and Control Inside U-groove -- Lack of fusion detection inside narrow U-groove -- Measuring Material Deformation using Digital Image Correlation -- Conclusions. |
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Sommario/riassunto |
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This book describes the application of vision-sensing technologies in welding processes, one of the key technologies in intelligent welding manufacturing. Gas tungsten arc welding (GTAW) is one of the main welding techniques and has a wide range of applications in the manufacturing industry. As such, the book also explores the application of AI technologies, such as vision sensing and machine |
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learning, in GTAW process sensing and feature extraction and monitoring, and presents the state-of-the-art in computer vision, image processing and machine learning to detect welding defects using non-destructive methods in order to improve welding productivity. Featuring the latest research from ORNL (Oak Ridge National Laboratory) using digital image correlation technology, this book will appeal to researchers, scientists and engineers in the field of advanced manufacturing. |
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