This book addresses the needs of researchers and practitioners in the field of high-speed trains, especially those whose work involves safety and reliability issues in traction systems. It will appeal to researchers and graduate students at institutions of higher learning, research labs, and in the industrial R&D sector, catering to a readership from a broad range of disciplines including intelligent transportation, electrical engineering, mechanical engineering, chemical engineering, the biological sciences and engineering, economics, ecology, and the mathematical sciences.

This book describes the wave characteristics of contact lines taking wind into consideration and discusses new methods for detecting catenary geometry, pantograph slide fault, and catenary support system faults. It also introduces wire-irregularity detection methods for catenary estimation, and discusses modern spectrum estimation tools for catenary. It is organized in three parts: the first discusses statistical characteristics of pantograph-catenary data, such as stationarity, periodicity, correlation, high-order statistical properties and wave characteristics of contact lines, which are the basis of pantograph-catenary relationship analysis. The second part includes geometry parameter detection and support-system fault detection in catenary, as well as slide-fault detection in pantographs, and presents some new detection algorithms and plans. The final part addresses catenary estimation, including detection of contact-line wire irregularities and estimation of catenary based on spectrum, and presents detection methods for contact-line irregularity and modern spectrum estimation tools for catenary.

This book reflects the latest research trends, methods, and experimental results in the field of electrical and information technologies for rail transportation, which covers abundant state-of-the-art research theories and ideas. As a vital field of research that is highly relevant to current developments in a number of technological domains, the subjects it covered include intelligent computing, information processing, communication technology, automatic control, etc. The objective of the proceedings is to provide a major interdisciplinary forum for researchers, engineers, academicians, and industrial professionals to present the most innovative research and development in the field of rail transportation electrical and information technologies. Engineers and researchers in academia, industry, and government will also explore an insightful view of the solutions that combine ideas from multiple disciplines in this field. The volumes serve as an excellent reference work for researchers and graduate students working on rail transportation and electrical and information technologies.

Safe and high-efficiency operation are two main issues in rail transportation. This book focuses on these two key issues, bringing together a wealth of research to offer theoretical and technical support for rail operations and maintenance. In addition, it presents a comprehensive active safety assurance system for rail transportation, which includes the quantitative state identification and prediction of train components; rail transportation safety and reliability assessment methods; and rail transportation risk assessment at the rail networks level, which achieves the quantitative and high-precision monitoring of complex systems in real-time. In addition, it extends active safety based theory to safety prognostic analysis in the traffic system. Lastly, representative case studies verify that the theory is suitable for the actual traffic system.

Data-Driven and Model-Based Methods for Fault Detection and Diagnosis covers techniques that improve the quality of fault detection and enhance monitoring through chemical and environmental processes. The book provides both the theoretical framework and technical solutions. It starts with a review of relevant literature, proceeds with a detailed description of developed methodologies, and then discusses the results of developed methodologies, and ends with major conclusions reached from the analysis of simulation and experimental studies. The book is an indispensable resource for researchers in academia and industry and practitioners working in chemical and environmental engineering to do their work safely. Outlines latent variable based hypothesis testing fault detection techniques to enhance monitoring processes represented by linear or nonlinear input-space models (such as PCA) or input-output models (such as PLS) Explains multiscale latent variable based hypothesis testing fault detection techniques using multiscale representation to help deal with uncertainty in the data and minimize its effect on fault detection Includes interval PCA (IPCA) and interval PLS (IPLS) fault detection methods to enhance the quality of fault detection Provides model-based detection techniques for the improvement of monitoring processes using state estimation-based fault detection approaches Demonstrates the effectiveness of the proposed strategies by conducting simulation and experimental studies on synthetic data