Editors:
- Presents fault diagnosis methods from FDI and DX research communities
- Introduces advanced topics currently still being researched, including methods for non-linear, hybrid and discrete-event systems
- Provides a glimpse of the fundamental issues and techniques from the artificial intelligence and control fields
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Table of contents (18 chapters)
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Front Matter
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Standard Approaches
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Front Matter
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Advanced Approaches
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Front Matter
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About this book
Fault Diagnosis of Dynamic Systems is valuable source of information for researchers and engineers starting to work on fault diagnosis and willing to have a reference guide on the main concepts and standard approaches on fault diagnosis. Readers with experience on one of the two main communities will also find it useful to learn the fundamental concepts of the other community and the synergies between them. The book is also open to researchers or academics who are already familiar with the standard approaches, since they will find a collection of advanced approaches with more specific and advanced topics or with application to different domains. Finally, engineers and researchers looking for transferable fault diagnosis methods will also find useful insights in the book.
Editors and Affiliations
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Research Center for Supervision, Safety and Automatic Control (CS2AC), Universitat Politècnica de Catalunya (UPC), Terrassa, Spain
Teresa Escobet, Vicenç Puig
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Department of Computer Science, University of Valladolid, Segovia, Spain
Anibal Bregon
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Department of Computer Science, University of Valladolid, Valladolid, Spain
Belarmino Pulido
About the editors
Dr. Anibal Bregon received his B.Sc., M.Sc. and Ph.D. degrees in Computer Science from the University of Valladolid (Spain) in 2005, 2007 and 2010, respectively. He joined the Department of Computer Science at the University of Valladolid in 2011, where he is Associate Professor since February 2018. He has carried out both basic and applied research in the areas of fault diagnosis and prognosis for aerospace and industrial systems, has co-authored more than 80 journal and conference papers, and has participated on several funded projects, networks and contracts on fault diagnosis and prognosis topics, and on Big Data analytics. He has been guest researcher with the Intelligent Systems Division at NASA Ames Research Center and the Institute for Software Integrated Systems at Vanderbilt University, among others. His current research interests include model-based reasoning for diagnosis and prognosis, health-management, Big Data and Industry 4.0. Among various other professional activities, he has held different chair positions at the PHM and PHME conferences, has been IPC member of several conferences, such as DX and PHM, has been co-administrator of several courses and summer schools on diagnosis, prognosis, and artificial intelligence, and has been the Local Chair of the 2016 European Conference of the Prognostics and Health Management Society.
Prof. Belarmino Pulido received his Engineering degree, M.Sc. degree, and Ph.D. degree in Computer Science from the University of Valladolid, Valladolid, Spain, in 1992, 1995, and 2001 respectively. In 1994 he joined the Department of Computer Science at the University of Valladolid, where he is Associate Professor since 2002. His main research interests are Model-based reasoning and Knowledge-based reasoning, and their application to Supervision and Diagnosis. Currently he is working in model-based diagnosis and prognosis of distributed hybrid systems. He is the coordinator of the Spanish Network on Supervision and Diagnosis of Complex Systems since 2005. He has worked in different regional (3) national (16) and European/international (3) funded projects related to Supervision and Diagnosis, being the main researcher in 6. He has been the supervisor of 2 PhD Theses and 2 MsC Theses on model-based diagnosis, has published 26 papers in JCR journals/publications, 9 papers on non JCR journals, 53 international and 24 national conference papers. He has been IPC member on serveral conferences such as DX or ECAI. He organized DX-06. Moreover, he is regular reviewer for different journals related with AI and diagnosis: IEEE Trans. on Syst. Man and Cybernetics (with different name changes), AI Comm, Eng. Apps. of Artificial Intelligence, etc. and also reviewer for IFAC, Safeprocess or ECC conferences.
Prof. Vicenç Puig received a Telecommunications Engineering B.sc./M.sc. Degree in 1993 and a PhD degree in Automatic Control, Vision, and Robotics in 1999, both from Universitat Politècnica de Catalunya (UPC). He is Full Professor of the Automatic Control Department (ESAII) and Researcher of Institut de Robòtica i Informàtica Industrial (IRI) at UPC. He is currently the Director of the Automatic Control Department since 2015 and the Head of the research group on advanced control systems (SAC) since 2007 at UPC. He has developed important scientific contributions in the areas of fault diagnosis and fault tolerant control using interval and linear-parameter-varying models with set-based approaches. He has participated in more than 20 European and national research projects in the last decade. He has also led many private contracts with several companies and has published more than 100 journal articles as well as 450 papers in international conference/workshop proceedings. He has supervised over 21 PhD dissertations and more than 40 Master’s theses/final projects. He is currently the Vice-chair of the IFAC Safeprocess TC Committee 6.4 since 2014. He has been the Chair of the 3rd IEEE Conference on Control and Fault-Tolerant Systems (Systol 2016) and the IPC Chair of IFAC Safeprocess 2018. He is also Associate Editor of the International Journal of Robust and Non-linear Control and ISA Transactions.
Bibliographic Information
Book Title: Fault Diagnosis of Dynamic Systems
Book Subtitle: Quantitative and Qualitative Approaches
Editors: Teresa Escobet, Anibal Bregon, Belarmino Pulido, Vicenç Puig
DOI: https://doi.org/10.1007/978-3-030-17728-7
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-17727-0Published: 03 July 2019
Softcover ISBN: 978-3-030-17730-0Published: 14 August 2020
eBook ISBN: 978-3-030-17728-7Published: 22 June 2019
Edition Number: 1
Number of Pages: XV, 462
Number of Illustrations: 96 b/w illustrations, 89 illustrations in colour
Topics: Control and Systems Theory, Systems Theory, Control, Industrial Chemistry/Chemical Engineering, Quality Control, Reliability, Safety and Risk, Automotive Engineering