Overview
- Covers recent developments in predictive maintenance, including basic algorithms and methods, required notions, and definitions
- Discusses problems in application domains such as on-line production lines, factories of the future, , IoT, power plants and turbines, conditioning systems, railway infrastructures, equipment and tool monitoring, and energy facilities
- Studies the links between methods and techniques as well as open challenges of predictive maintenance, addresses early fault detection, prognostics and diagnosis, and optimization and self–healing techniques for on-line decision support tools in dynamic systems
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Table of contents (18 chapters)
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Anomaly Detection and Localization
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Prognostics and Forecasting
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Diagnosis, Optimization and Control
Keywords
About this book
Editors and Affiliations
About the editors
Moamar Sayed-Mouchaweh received his Master degree from the University of Technology of Compiegne-France in 1999. Then, he received his PhD degree from the University of Reims-France in December 2002. He was working as Associated Professor in Computer Science, Control and Signal processing at the University of Reims-France in the Research center in Sciences and Technology of the Information and the Communication (CReSTIC). In December 2008, he obtained the Habilitation to Direct Researches (HDR) in Computer science, Control and Signal processing. Since September 2011, he is working as a Full Professor in the High National Engineering School of Mines “Ecole Nationale Supérieure des Mines de Douai” at the Department of Computer Science and Automatic Control (Informatique & Automatique). He edited the Springer book Learning in Non-Stationary Environments: Methods and Applications, in April 2012 and wrote two Brief Springer books in Electrical and Computer Engineering: Discrete Event Systems: Diagnosis and Diagnosability, and Learning from Data Streams in Dynamic Environments. He was a guest editor of several special issues of international journals. He was IPC Chair of the 12th IEEE International Conference on Machine Learning and Applications (ICMLA'13), the Conference Chair and IPC Chair of IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS2015), and the IPC Chair of the 15th IEEE International Conference on Machine Learning and Applications (ICMLA'16). He is working as a member of the Editorial Board of Elsevier Journal Applied Soft Computing and Springer Journals Evolving Systems and Intelligent Industrial Systems.
Bibliographic Information
Book Title: Predictive Maintenance in Dynamic Systems
Book Subtitle: Advanced Methods, Decision Support Tools and Real-World Applications
Editors: Edwin Lughofer, Moamar Sayed-Mouchaweh
DOI: https://doi.org/10.1007/978-3-030-05645-2
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-05644-5Published: 12 March 2019
eBook ISBN: 978-3-030-05645-2Published: 28 February 2019
Edition Number: 1
Number of Pages: XIII, 567
Number of Illustrations: 56 b/w illustrations, 144 illustrations in colour
Topics: Communications Engineering, Networks, Quality Control, Reliability, Safety and Risk, Control and Systems Theory, Computational Intelligence, Information Systems and Communication Service