Bøger i Advances in High-Speed Rail Te serien

The second edition of this book systematically summarizes the latest research findings on high-speed railway track dynamics, made by the author and his research team over the past decade. It explores cutting-edge issues concerning the basic theory of high-speed railways, covering the dynamic theories, models, algorithms and engineering applications of the high-speed train and track coupling system.Presenting original concepts, systematic theories and advanced algorithms, the book places great emphasis on the precision and completeness of its content. The chapters are interrelated yet largely self-contained, allowing readers to either read through the book as a whole or focus on specific topics. It also combines theories with practice to effectively introduce readers to the latest research findings and developments in high-speed railway track dynamics. It offers a valuable resource for researchers, postgraduates and engineers in the fields of civil engineering, transportation, highway and railway engineering.

This book focuses on the deep learning technologies and their applications in the catenary detection of high-speed railways. As the only source of power for high-speed trains, the catenary's service performance directly affects the safe operation of high-speed railways. This book systematically shows the latest research results of catenary detection in high-speed railways, especially the detection of catenary support component defect and fault. Some methods or algorithms have been adopted in practical engineering. These methods or algorithms provide important references and help the researcher, scholar, and engineer on pantograph and catenary technology in high-speed railways. Unlike traditional detection methods of catenary support component based on image processing, some advanced methods in the deep learning field, including convolutional neural network, reinforcement learning, generative adversarial network, etc., are adopted and improved in this book. The main contents include the overview of catenary detection of electrified railways, the introduction of some advance of deep learning theories, catenary support components and their characteristics in high-speed railways, the image reprocessing of catenary support components, the positioning of catenary support components, the detection of defect and fault, the detection based on 3D point cloud, etc.

This book explores the mechanisms behind high-speed railway (HSR) traffic accidents caused by natural disasters, employing the concept of ¿dynamic tracking, situation assessment, and early warning management¿. It establishes a natural disaster warning system for ensuring the safety of HSR operations, while providing insightful management measures and methods that address the challenges posed by natural disasters. By analyzing the current state and objective circumstances of HSR safety operations, this book distinguishes itself from similar publications both domestically and internationally. It conducts an in-depth analysis of the safe operation of high-speed railways by adopting a systems science approach that effectively merges theory with practical applications. Furthermore, the book explores the developmental trajectory of high-speed railways and investigates the determination of their safe operation. It comprehensively evaluates the safety of high-speed railway operations by employing mathematical theories of uncertainty, subsequently presenting detailed measures to effectively tackle safety concerns related to high-speed railways.