Key technologies of intelligentized welding manufacturing : visual sensing of weld pool dynamic characters and defect prediction of GTAW process / Zongyao Chen, Zhili Feng, Jian Chen.
2021
TS227 .C54 2021eb
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Title
Key technologies of intelligentized welding manufacturing : visual sensing of weld pool dynamic characters and defect prediction of GTAW process / Zongyao Chen, Zhili Feng, Jian Chen.
Author
Chen, Zongyao.
ISBN
9789811564918 (electronic bk.)
9811564914 (electronic bk.)
9789811564925 (print)
9811564922
9789811564932 (print)
9811564930
9811564906
9789811564901
9811564914 (electronic bk.)
9789811564925 (print)
9811564922
9789811564932 (print)
9811564930
9811564906
9789811564901
Published
Singapore : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource (xiii, 95 pages)
Item Number
10.1007/978-981-15-6491-8 doi
Call Number
TS227 .C54 2021eb
Dewey Decimal Classification
671.5/2
Summary
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 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.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Added Author
Feng, Zhili.
Chen, Jian.
Chen, Jian.
Available in Other Form
Print version: 9789811564901
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Table of Contents
Introduction
Monitoring of Weld Pool Surface with Active Vision
Visual Sensing of 3D Weld Pool Geometry with Passive Vision Image
Penetration prediction with machine learning models
Penetration Control for Bead-on plate welding
Penetration Detection of narrow U-groove welding
Lack of fusion detection inside narrow U-groove
Conclustions and recommendations.
Monitoring of Weld Pool Surface with Active Vision
Visual Sensing of 3D Weld Pool Geometry with Passive Vision Image
Penetration prediction with machine learning models
Penetration Control for Bead-on plate welding
Penetration Detection of narrow U-groove welding
Lack of fusion detection inside narrow U-groove
Conclustions and recommendations.