Data-driven Detection and Diagnosis of Faults in Traction Systems of High-speed Trains

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Hongtian Chen Bin Jiang

Data-driven Detection and Diagnosis of Faults in Traction Systems of High-speed Trains

Hongtian Chen, Bin Jiang, Ningyun Lu , Wen Chen

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English

Springer Nature Switzerland AG
26 April 2020

Railway transport industries; Automatic control engineering; Intelligent & automated transport system technology; Artificial intelligence

Series: Lecture Notes in Intelligent Transportation and Infrastructure

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.

By: Hongtian Chen, Bin Jiang, Ningyun Lu, Wen Chen
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Edition: 2020 ed.
Dimensions: Height: 235mm, Width: 155mm,
Weight: 454g
ISBN: 9783030462628
ISBN 10: 3030462625
Series: Lecture Notes in Intelligent Transportation and Infrastructure
Pages: 160
Publication Date: 26 April 2020
Audience: College/higher education , Professional and scholarly , Further / Higher Education , Undergraduate
Format: Hardback
Publisher's Status: Active

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.