Data-driven detection and diagnosis of faults in traction systems of high-speed trains / / Hongtian Chen, Bin Jiang, Ningyun Lu, Wen Chen

• Autore: Chen Hongtian
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
• Edizione: 1st ed. 2020.
• Descrizione fisica: 1 online resource (xiii, 160 pages) : illustrations
• Disciplina: 385.22
• Soggetto topico: Fault location (Engineering); High speed trains
• Persona (resp. second.): JiangBin <1966->; LuNingyun; ChenWen
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Data-driven Detection and Diagnosis of Faults in Traction Systems of High-speed Trains
• ISBN: 3-030-46263-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910392740503321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Intelligent Transportation and Infrastructure, . 2523-3440