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Book
Deep learning-based detection of catenary support component defect and fault in high-speed railways
Authors: --- ---
ISBN: 9819909538 981990952X Year: 2023 Publisher: Singapore : Springer Nature Singapore Pte Ltd.,

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Abstract

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.

Keywords

Railroad engineering. --- Machine learning. --- Signal processing. --- Quantitative research. --- Transportation engineering. --- Traffic engineering. --- Artificial intelligence. --- Rail Vehicles. --- Machine Learning. --- Signal, Speech and Image Processing . --- Data Analysis and Big Data. --- Transportation Technology and Traffic Engineering. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Engineering, Traffic --- Road traffic --- Street traffic --- Traffic, City --- Traffic control --- Traffic regulation --- Urban traffic --- Highway engineering --- Transportation engineering --- Civil engineering --- Engineering --- Data analysis (Quantitative research) --- Exploratory data analysis (Quantitative research) --- Quantitative analysis (Research) --- Quantitative methods (Research) --- Research --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Learning, Machine --- Artificial intelligence --- Engineering, Railroad --- Railroads --- Deep learning (Machine learning) --- Fault location (Engineering) --- High speed trains. --- Bullet trains --- Metroliners --- Trains, High speed --- Turbotrains --- High speed ground transportation --- Railroad trains --- Location of system faults --- System fault location (Engineering) --- Dynamic testing --- Learning, Deep (Machine learning) --- Iterative methods (Mathematics) --- Machine learning


Multi
Deep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways
Authors: --- ---
ISBN: 9789819909537 9789819909520 9789819909544 9789819909551 Year: 2023 Publisher: Singapore Springer Nature

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Abstract

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.

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