Data-Driven Technology for Engineering Systems Health Management Des
This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven meth
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Data-Driven Technology for Engineering Systems Health Management Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions
Data-Driven Technology for Engineering Systems Health Management
Gang Niu
Data-Driven Technology for Engineering Systems Health Management Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decision
123
Gang Niu Institute of Rail Transit Tongji University Shanghai China
ISBN 978-981-10-2031-5 DOI 10.1007/978-981-10-2032-2
ISBN 978-981-10-2032-2
(eBook)
Jointly published with Science Press, Beijing, China Library of Congress Control Number: 2016946012 © Springer Science+Business Media Singapore and Science Press, Beijing, China 2017 This work is subject to copyright. All rights are reserved by the Publishers, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer Science+Business Media Singapore Pte Ltd.
Preface
Systems health management (SHM) has emerged over recent years as significant technologies that are making an impact on both military and commercial maintenance practices. This discipline links studies of failure mechanisms to system lifecycle management and is often referred to as prognostics and health management (PHM), or in transportation applications—vehicle health management (VHM). Technical approaches to building models in SHM/PHM can be categorized broadly into data-driven approach, model-based approach, and hybrid approach. The data-driven approach for SHM/PHM is also explained in condition-based maintenance (CBM). CBM can be applied as a technical architecture and engineering strategy of data-driven PHM. In this book, data-driven PHM/CBM is introduced in details, which mainly emphasis functions of condition monitoring, fault diagnosis, and prognosis. Condition monitoring, fault diagnosis, and prognosis of engineering systems have received considerable attention in recent years and are increasingly becoming important in industry because of
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