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This book offers a timely collection of chapters on innovative research and education-focused developments in the vast field of rail transport, including rail operations, management, economics, and sustainable infrastructure. Adding on the tradition of the previous four volumes, here a special emphasis is given on the current needs for rail skills development, innovating rail higher education provision, and solutions aimed at bridging the gap between railway education and industry expectations. Strategies for making the rail sector more attractive to early careers and younger generations, and methods to identify and retain talents in the railway sector are also described. Gathering peer-reviewed contributions prepared by the RailUniNet and AstonRail strategic partnership members, this book offers a timely view on current developments on rail-focused teaching and learning methods and approaches with extensive information for both academics and professionals specialising in railway research, technologies, training and education.
Railroad engineering. --- Railroads --- Sustainable transportation. --- Technological innovations. --- Transportation engineering. --- Traffic engineering. --- Technical education. --- Sustainability. --- Transportation Technology and Traffic Engineering. --- Rail Vehicles. --- Engineering and Technology Education.
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629.11 --- 629 --- autoband; krachtwerking --- dynamica; auto --- kinematica; auto --- trilling; auto (vibratie; auto) --- 629 Transport vehicle engineering --- Transport vehicle engineering --- 629.11 Land vehicle engineering (except rail vehicles). Road vehicles --- Land vehicle engineering (except rail vehicles). Road vehicles --- (zie ook: nvh) --- (zie ook: schokdemper)
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TECHNOLOGY & ENGINEERING --- Automotive --- Automobiles --- Automobile industry and trade --- Mechanical Engineering --- Engineering & Applied Sciences --- Automotive Engineering --- Energy consumption --- Research --- Government policy --- 629.11 --- Land vehicle engineering (except rail vehicles). Road vehicles --- 629.11 Land vehicle engineering (except rail vehicles). Road vehicles --- Partnership for a New Generation of Vehicles (U.S.) --- Autos (Automobiles) --- Cars (Automobiles) --- Gasoline automobiles --- Motorcars (Automobiles) --- PNGV --- U.S. Council for Automotive Research. --- United States. --- Motor vehicles --- Transportation, Automotive --- U.S. Council for Automotive Research --- E-books
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This textbook examines key railway engineering topics useful for railway design and control. Conventional railways are considered together with high-speed railways, tramways, metros, maglev and hyperloop systems, people movers, monorails and rack railways. Every system of transport is described in its basic technical characteristics, especially in terms of transportation system capacity, alignment design criteria and construction costs. It is an introductory book to specific topics of the railway engineering field, and thus, the mathematical treatment is purposely brief and simplified. The book is an ideal learning resource for students of civil engineering, as well as a valuable reference for practicing engineers involved with railway designs.
Transportation engineering. --- Traffic engineering. --- Railroad engineering. --- Security systems. --- Transportation Technology and Traffic Engineering. --- Rail Vehicles. --- Security Science and Technology. --- Security measures --- Burglary protection --- Engineering, Railroad --- Railroads --- Transportation engineering --- Engineering, Traffic --- Road traffic --- Street traffic --- Traffic, City --- Traffic control --- Traffic regulation --- Urban traffic --- Highway engineering --- Civil engineering --- Engineering --- Design and construction. --- Construction --- Railroad Engineering --- Technology & Engineering
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The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product.
Technology: general issues --- Kalman filter --- motion capture --- gait analysis --- inertial sensor --- rail vehicles --- track irregularities --- multibody dynamics --- inertial sensors --- computer vision --- singular configuration --- parallel robot --- motion control --- 3D tracking --- screw theory --- Kalman filtering --- coupled states-inputs estimation --- virtual sensors --- slider-crank mechanism --- virtual sensoring --- physical sensors --- smart/intelligent sensors --- sensor technology and applications --- sensing principles --- signal processing in sensor systems --- symbolic generation --- real-time computation --- human-in-the-loop --- haptic devices --- parameter estimation --- curve fitting method --- hydraulic system --- predictive maintenance --- characteristic curve --- product life cycle --- digital twin --- adaptive Kalman filter --- nonlinear models --- virtual sensing --- multibody based observers --- vehicle dynamics estimation --- sideslip angle estimation --- factor graph --- graphical models --- movable repetitive lander --- fault-tolerant soft-landing --- landing configuration --- stability optimization --- n/a
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The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product.
Technology: general issues --- Kalman filter --- motion capture --- gait analysis --- inertial sensor --- rail vehicles --- track irregularities --- multibody dynamics --- inertial sensors --- computer vision --- singular configuration --- parallel robot --- motion control --- 3D tracking --- screw theory --- Kalman filtering --- coupled states-inputs estimation --- virtual sensors --- slider-crank mechanism --- virtual sensoring --- physical sensors --- smart/intelligent sensors --- sensor technology and applications --- sensing principles --- signal processing in sensor systems --- symbolic generation --- real-time computation --- human-in-the-loop --- haptic devices --- parameter estimation --- curve fitting method --- hydraulic system --- predictive maintenance --- characteristic curve --- product life cycle --- digital twin --- adaptive Kalman filter --- nonlinear models --- virtual sensing --- multibody based observers --- vehicle dynamics estimation --- sideslip angle estimation --- factor graph --- graphical models --- movable repetitive lander --- fault-tolerant soft-landing --- landing configuration --- stability optimization --- n/a
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The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product.
Kalman filter --- motion capture --- gait analysis --- inertial sensor --- rail vehicles --- track irregularities --- multibody dynamics --- inertial sensors --- computer vision --- singular configuration --- parallel robot --- motion control --- 3D tracking --- screw theory --- Kalman filtering --- coupled states-inputs estimation --- virtual sensors --- slider-crank mechanism --- virtual sensoring --- physical sensors --- smart/intelligent sensors --- sensor technology and applications --- sensing principles --- signal processing in sensor systems --- symbolic generation --- real-time computation --- human-in-the-loop --- haptic devices --- parameter estimation --- curve fitting method --- hydraulic system --- predictive maintenance --- characteristic curve --- product life cycle --- digital twin --- adaptive Kalman filter --- nonlinear models --- virtual sensing --- multibody based observers --- vehicle dynamics estimation --- sideslip angle estimation --- factor graph --- graphical models --- movable repetitive lander --- fault-tolerant soft-landing --- landing configuration --- stability optimization --- n/a
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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.
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
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