Metal Surface Quality Detection System
Description
This book focus on the theoretical introduction of multispectral multidimensional imaging technology and, combined with the internationally advanced artificial intelligence technology system, systematically elaborate on its cutting-edge theoretical methods and application achievements in the surface quality perception process of metal materials for the first time. The content covers core algorithms such as multispectral imaging, multi-information fusion, image processing, and artificial intelligence, comprehensively presenting the technical connotation of surface quality in the production and processing of metal materials empowered by artificial intelligence.
This book also provide an in-depth analysis of the multidisciplinary knowledge systems involved, including optical imaging, 3D imaging, multi-information fusion, deep learning, image processing, and surface quality inspection, and explain them with practical cases. In terms of chapter structure, to facilitate engineers, technicians, and students from different professional backgrounds to grasp the relevant content, this book will first introduce the necessary preliminary knowledge, followed by a systematic explanation of machine vision, 3D imaging, detection algorithms, application effects, and other topics, aiming to foster the cultivation of interdisciplinary talent.
More details
Persons
Dr. Dongdong Zhou is an Associate Professor of the Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing (USTB), China. And also is the specially invited Researcher in Yangjiang alloy material laboratory, Yangjiang, Guangdong Province, China. He received the B.Sc. degree in Metallurgical Engineering from Kunming University of Science and Technology, Kunming, China in 2007, and the Ph.D. degree in Metallurgical Engineering from USTB, Beijing, China in 2018. He has published over 20 refereed papers. Zhou's current research interests include basic research and industrial application of machine vision, defect detection, artificial intelligence, spectral detection technologies. He also is the member of Chinese Society for Metals, Chinese Optical Society, Chinese Artificial Intelligence Society, Chinese Society of Image and Graphics. He is currently serving as reviewers of FUEL?ISIJ?IEEE/CAA Journal of Automatica Sinica?International Journal of Chemical Reactor Engineering?Sensors.
Dr. Jie Chen, Professorate Senior Engineer, MCC Central Research Institute of Building and Construction Co., Ltd., Presided over one project under the National Key R&D Program and one scientific and technological support project of the Certification and Accreditation Administration; participated as a core team member in 13 national and provincial/ministerial-level projects; successively completed a series of technical achievements including the development of advanced testing methods and equipment, establishment of steel quality evaluation rules, and optimization of construction steel production processes; contributed as a key technical to establishing China's standard system for construction steel products, testing, and applications.
Prof. Ke Xu is currently working as an Professor in Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing (USTB), China. He received his PhD degree in Mechanical Engineering from USTB, China in 1998, then Visiting research at RWTH Aachen University, Germany as a postdoctoral researcher in 1998 to 2000. His main research interests include machine vision, industrial inspection, intelligent manufacturing. He has published over 200 SCI journal articles, 2 books and over 1000 Web of Science citations. He has been selected into the Ministry of Education's "New Century Excellent Talents", Beijing's "Science and Technology Rising Stars" program, and won the title of "Metallurgy Youth Science and Technology Award" by the Chinese Society for Metals.
Dr. Fujian Guo is the Minister of Research and Development Yangjiang alloy material laboratory, Yangjiang, Guangdong Province, China. He got the bachelor's degree in Materials Science and Engineering from University of Science and Technology Beijing, Beijing, China in 2011, and the PhD degree in Materials Science and Engineering from University of Science and Technology Beijing, Beijing, China in 2020. Dr. Yuan is mainly engaged in the research of steel for offshore engineering and alloy materials for people's livelihood (martensitic stainless steel). He has published over 15 papers in Materials and Design?Materials Science and Engineering A?Steel research International, and 2 invention patents.
Content
Introduction to the Development History of Online Surface Quality Inspection.- High-Speed Laser Centerline Extraction and Heterogeneous Measurement Architectures for Low Cost Hardware.- Effects of Camera External Parameters Error on Measurement Accuracy in Monocular Vision.- Directional Edge Detection Algorithm Based on Gaussian Function Weighting.- A Few-Shot Steel Surface Defect Generation Method Based on Diffusion Models.- Outer Surface Defect Detection of Steel Pipes with 3D Vision Based on Multi-Line Structured Lights.- PNG An Adaptive Local Global Hybrid Framework for Unsupervised Material Surface Defect Detection.- Unsupervised Surface Defect Detection of Aluminum Sheets with Combined Bright-Field and Dark Field Illumination.- LarGAN A Label Auto Rescaling Generation Adversarial Network for Rare Surface Defects.- A Self-Supervised Model Based on CutPaste Mix for Ductile Cast Iron Pipe Surface Defect Classification.- Automatic Measurement of External Thread at the End of Sucker Rod Based on Machine Vision.- Depth Extraction of 3D Defects on Curved Surfaces
with Multi-Line Lasers.