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Data-driven Detection and Diagnosis of Faults in Traction Systems of High-speed Trains / / Hongtian Chen, Bin Jiang, Ningyun Lu, Wen Chen

By: Chen, Hongtian, autor
Contributor(s): Jiang, Bin, (1966-), autor | Lu, Ningyun, autor | Chen, Wen, autor | SpringerLink (Online service)
Material type: materialTypeLabelE-bookSeries: (Lecture Notes in Intelligent Transportation and Infrastructure, 2523-3440); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: First edition.Description: 1 recurso en línea (XIII, 160 páginas) : 53 ilustraciones, 47 ilustraciones a color.ISBN: 9783030462635.Subject: Ferrocarriles de alta velocidad | Diagnóstico de fallosOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Traction Systems and Experimental Platforms -- Basics of Data-driven FDD Methods -- Multi-mode PCA-based FDD Methods -- Probability-relevant PCA-based FDD Methods -- Deep PCA-based FDD Methods -- PCA and Kull back-Leibler Divergence-based FDD Methods -- PCA and Hellinger Distance-based FDD Methods -- Conclusions and Further Work. .
Abstract: 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. .
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TF1450 2020 EB (Browse shelf(Opens below)) Acceso electrónico eBook.24062033
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Introduction -- Traction Systems and Experimental Platforms -- Basics of Data-driven FDD Methods -- Multi-mode PCA-based FDD Methods -- Probability-relevant PCA-based FDD Methods -- Deep PCA-based FDD Methods -- PCA and Kull back-Leibler Divergence-based FDD Methods -- PCA and Hellinger Distance-based FDD Methods -- Conclusions and Further Work. .

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. .

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