The primary aim of this volume is to provide researchers and engineers from both academic and industry with up-to-date coverage of new results in the field of robotic welding, intelligent systems and automation. The book is mainly based on papers selected from the 2019 International Workshop on Intelligentized Welding Manufacturing (IWIWM’2019) in USA. The articles show that the intelligentized welding manufacturing (IWM) is becoming an inevitable trend with the intelligentized robotic welding as the key technology. The volume is divided into four logical parts: Intelligent Techniques for Robotic Welding, Sensing of Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, as well as Intelligent Control and its Applications in Engineering.
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Multi-layer Multi-pass Welding of Medium Thickness Plate: Technologies, Advances and Future Prospects |
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3 | (32) |
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A Review: Application Research of Intelligent 3D Detection Technology Based on Linear-Structured Light |
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35 | (14) |
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Acoustic Emission-Based Weld Crack In-situ Detection and Location Using WT-TDOA |
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49 | (26) |
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The Research of Real-Time Welding Quality Detection via Visual Sensor for MIG Welding Process |
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75 | (12) |
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A Weld Bead Profile Extraction Method Based on Scanning Monocular Stereo Vision for Multi-layer Multi-pass Welding on Mid-thick Plate |
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87 | (12) |
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The Intelligent Methodology for Monitoring the Dynamic Welding Quality Using Visual and Audio Sensor |
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99 | (16) |
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Convolutional Neural Network Prediction of Aluminum Alloy GTAW Penetration Process Based on Arc Sound Sensing |
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115 | (16) |
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Identification and Penetration Prediction of Aluminum Alloy GTAW Pool Based on Network Vision Monitoring |
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131 | (18) |
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Research on Welding Transient Deformation Monitoring Technology Based on Non-contact Sensor Technology |
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149 | (14) |
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Binocular Stereo Vision and Modified DBSCAN on Point Clouds for Single Leaf Segmentation |
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163 | (20) |
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Short Papers and Technical Notes |
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Teaching-Free Intelligent Robotic Welding of Heterocyclic Medium and Thick Plates Based on Vision |
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183 | (10) |
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In-Process Visual Monitoring of Penetration State in Nuclear Steel Pipe Welding |
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193 | (8) |
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| Information for Authors |
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201 | (2) |
| Author Index |
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203 | |
Dr. Shanben Chen (SB 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. Yuming Zhang - FAWS, FASME, FSME, SIEEE, Professor and James Boyd Professor in Electrical Engineering - has been with the University of Kentucky, Lexington, USA since 1991, and became a Full Professor in 2005. He received his BS and MS degrees in control theory and application from Harbin Institute of Technology (HIT), China, where he completed his PhD degree in welding in 1990. He has published 180 peer-reviewed journal papers and holds 8 US patents. Dr. Zhili Feng leads the Materials Joining Team, and is a Distinguished R&D Staff at Oak Ridge National Laboratory, where he manages 10 scientists and supporting staff, conducting both fundamental and applied R&D and pursuing technological innovations for diverse interdisciplinary subjects related to materials joining and materials manufacturing processes, with an annual R&D budget of $15 million.
