Detection And Estimation Research Of High Speed Railway Catenary
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Detection and Estimation Research of High-speed Railway Catenary
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.
Deep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways
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.
International Symposium for Intelligent Transportation and Smart City (ITASC) 2017 Proceedings
This book presents research advances in intelligent transportation and smart cities in detail, mainly focusing on green traffic and urban utility tunnels, presented at the 3rd International Symposium for Intelligent Transportation and Smart City (ITASC) held at Tongji University, Shanghai, on May 19–20, 2017. It discusses a number of hot topics, such as the 2BMW system (Bus, Bike, Metro and Walking), transportation safety and environmental protection, urban utility design and application, as well as the application of BIM (Building Information Modeling) in city design. By connecting the theory and applications of intelligent transportation in smart cities, it enhances traffic efficiency and quality. The book gathers numerous selected papers and lectures, including contributions from respected scholars and the latest engineering advances, to provide guidance to researchers in the field of transportation and urban planning at universities and in related industries. The first conference in the ITASC series started in 2013 as a workshop of The International Symposium on Autonomous Decentralized System (ISADS), held in Mexico City, and the second was held in May 2015, in Tongji University, Shanghai.