Fault Diagnosis of Dynamic Systems

Quantitative and Qualitative Approaches

Teresa Escobet (Redaktør) ; Anibal Bregon (Redaktør) ; Belarmino Pulido (Redaktør) ; Vicenc Puig (Redaktør)

Fault Diagnosis of Dynamic Systems provides readers with a glimpse into the fundamental issues and techniques of fault diagnosis used by Automatic Control (FDI) and Artificial Intelligence (DX) research communities. Les mer
Vår pris
1688,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager

Paperback
Legg i
Paperback
Legg i
Vår pris: 1688,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager

Om boka

Fault Diagnosis of Dynamic Systems provides readers with a glimpse into the fundamental issues and techniques of fault diagnosis used by Automatic Control (FDI) and Artificial Intelligence (DX) research communities. The book reviews the standard techniques and approaches widely used in both communities. It also contains benchmark examples and case studies that demonstrate how the same problem can be solved using the presented approaches. The book also introduces advanced fault diagnosis approaches that are currently still being researched, including methods for non-linear, hybrid, discrete-event and software/business systems, as well as, an introduction to prognosis.
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.

Fakta

Innholdsfortegnelse

Introduction and Fundamental Concepts.- Case Studies.- Part I: Standard Approaches.- Structural Analysis.- The FDI Approach.- The DX Approach.- Bridge: Integration of FDI and DX Approaches.- Data-Driven Fault Diagnosis.- Discrete-Event Systems Fault Diagnosis.- Part II: Advanced Approaches.- Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems.- Model-Based Diagnosis with Probabilistic Models.- Qualitative Modeling for Fault Diagnosis.- Model Based Fault Diagnosis of Hybrid Systems.- Model-Based Software Debugging.- Diagnosing Business Processes.- Prognosis.

Om forfatteren

Prof. Teresa Escobet received her B.sc./M.sc. Degree in Industrial Engineering at UPC in 1989 and PhD at the same University in 1997. She began work at UPC as an Assistant Prof. in 1986 and she earned the status of Associate Prof. in 2001. Her teaching activities are related to issues of Automatic Control. She is a member of the research group "Advanced Control Systems (SAC)". Her main research interests are in dynamic system modelling and identification applied to fault detection, isolation, fault-tolerant control and condition-based maintenance. She has been involved in several International and national research projects and networks, and she has published more than 130 journal and conference papers and she has supervised 6 PhD dissertations. She has been NOC member of the 3rd IEEE Conference on Control and Fault-Tolerant Systems (Systol 2016).
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 pr