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Key Technologies of Intelligentized Welding Manufacturing: The Spectral Diagnosis Technology for Pulsed Gas Tungsten Arc Welding of Aluminum Alloys de Yiming Huang

Key Technologies of Intelligentized Welding Manufacturing: The Spectral Diagnosis Technology for Pulsed Gas Tungsten Arc Welding of Aluminum Alloys

Autor Yiming Huang, Shanben Chen
en Limba Engleză Hardback – 14 mai 2019
This book presents the recent research results of the application of arc spectrum in the welding process. It sheds light on the fundamentals of monitoring welding quality using arc spectral information. By analyzing the topic both from a global and local perspective, it establishes a knowledge base of features characterizing welding statuses. Researchers, scientists and engineers in the field of intelligent welding can benefit from the book. As such, this book provides valuable knowledge, useful methods, and practical algorithms that are applicable in real-time detection of welding defects.

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Specificații

ISBN-13: 9789811375484
ISBN-10: 9811375488
Pagini: 157
Ilustrații: XIII, 173 p. 151 illus., 132 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.44 kg
Ediția:1st ed. 2020
Editura: Springer Nature Singapore
Colecția Springer
Locul publicării:Singapore, Singapore

Cuprins

Introduction.- Monitoring principle of welding process based on arc emission spectrum.- Experimental setup made of welding and spectral acquisition subsystems.- Prediction of welding status based on features extracted from the whole arc spectrum.- Prediction of welding status based on features extracted from spectral lines of interest.- The control of welding quality based on spectral features.- Summary and conclusions.

Notă biografică

Dr. Yiming  Huang received his B.S. degree and Ph.D. degree in Materials Processing Engineering from the School of Materials Science and Engineering, Shanghai Jiao Tong University, in 2011 and 2017 respectively. He joined the School of Materials Science and Engineering, Tianjin University in 2017, and he is currently as a lecturer. His research interests include welding process modeling, machine learning, and defect detection. He has published several papers in international conferences and reputed journals in his research area.
Dr. Shanben Chen received his BS degree in industrial automation from Dalian Railway Institute (Dalian Jiao Tong University) in 1982, and received his MS and PhD in control theory and application from Harbin Institute of Technology, China, in 1987 and 1991, respectively. He worked as a postdoctoral fellow at the National Key Laboratory of Advanced Welding Production of China in Harbin Institute of Technology (HIT) from 1993 to 1995, and as a professor from 1995 to 2000.
From 2000 to present, he has served as the Special Professor, Cheung Kong Scholar Program of the Ministry of Education of China & Li Ka Shing Foundation, Hong Kong, and engaged at Shanghai Jiao Tong University, China, where he is also director of the Intelligentized Robotic Welding Technology Laboratory. Prof. Chen has also been a visiting professor at the University of Western Sydney (UWS) in connection with the ARC Linkage collaboration since 2009.
Currently, Prof. Chen is a senior member of the IEEE; a member of the American Welding Society; Chair of the Robotics & Automation Committee of the Chinese Welding Society (CWS); Deputy Secretary-General of the Chinese Welding Society; and a standing member of the Board of Directors, CWS.

Textul de pe ultima copertă

This book presents the recent research results of the application of arc spectrum in the welding process. It sheds light on the fundamentals of monitoring welding quality using arc spectral information. By analyzing the topic both from a global and local perspective, it establishes a knowledge base of features characterizing welding statuses. Researchers, scientists and engineers in the field of intelligent welding can benefit from the book. As such, this book provides valuable knowledge, useful methods, and practical algorithms that are applicable in real-time detection of welding defects.


Caracteristici

Focuses on the application of the welding arc spectrum in monitoring the process and the quality of arc welding Offers feature extraction algorithms for different kinds of welding defects Presents useful methods to develop on-line detection and improve the quality of the welding process