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Studies in Computational Intelligence

Fault Diagnosis Inverse Problems: Solution with Metaheuristics

Authors: Camps Echeverría, L., Llanes-Santiago, O., Campos Velho, H.F. de, Silva Neto, A.J.d.

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  • Presents solutions for fault diagnosis problems using an interdisciplinary perspective, combining inverse problem methodology and metaheuristics
  • Offers a systematic and clear overview of the main ideas, concepts and results in this field
  • Brings together tools from mathematics, physics, modeling, optimization and computational intelligence
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eBook $84.99
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  • ISBN 978-3-319-89978-7
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Hardcover $109.99
price for USA in USD
  • ISBN 978-3-319-89977-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $109.99
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  • ISBN 978-3-030-07908-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This book presents a methodology based on inverse problems for use in solutions for fault diagnosis in control systems, combining tools from mathematics, physics, computational and mathematical modeling, optimization and computational intelligence. This methodology, known as fault diagnosis – inverse problem methodology or FD-IPM, unifies the results of several years of work of the authors in the fields of fault detection and isolation (FDI), inverse problems and optimization. The book clearly and systematically presents the main ideas, concepts and results obtained in recent years. By formulating fault diagnosis as an inverse problem, and by solving it using metaheuristics, the authors offer researchers and students a fresh, interdisciplinary perspective for problem solving in these fields. Graduate courses in engineering, applied mathematics and computing also benefit from this work.

About the authors

Lídice Camps Echeverría holds bachelor’s and master’s degrees in Mathematics at Universidad de La Habana in 2006 and 2009 respectively.  She obtained the PhD in Engineering (2012), with minor in Automatics and Computer Science, at Universidad Tecnológica de La Habana José Antonio Echeverría, CUJAE, Cuba. Since 2006 she has pursued research at the Technological University of La Habana “José Antonio Echeverria” - CUJAE, Cuba. In 2011-2012, she undertook research at the National Institute for Space Research – INPE, Brazil, and at the Polytechnic Institute of Rio de Janeiro State University (IPRJ-UERJ). Her fields of interest include fault diagnosis and soft computing, with a focus on metaheuristics for optimization.
Orestes Llanes Santiago graduated from the Instituto Superior Politécnico “José Antonio Echeverría” – CUJAE, Cuba, in 1981. From 1989 to 1994, he studied at the Universidad de Los Andes, Venezuela, where he obtained a master’s degree in Control Engineering (1990) and a PhD in Applied Sciences (1994). He is currently a full professor and researcher at the Automation and Computing Department of the Faculty of Automation and Biomedical Electrical Engineering at the CUJAE. He is titular member of the  Academic of Sciences  of Cuba. His areas of interest are fault diagnosis in industrial systems, nonlinear control and computational intelligence with applications to control.
Haroldo Fraga de Campos Velho has a bachelor’s degree in Chemical Engineering from the Pontifical Catholic University of Rio Grande do Sul (1983), Brazil, and a master’s degree (1988) and a PhD (1992) in Mechanical Engineering, with a focus on Nuclear Reactor Physics and Computational Fluid Dynamics, respectively, both from the Federal University of Rio Grande do Sul. He has been a researcher at the Computing and Applied Mathematics Laboratory of the National Institute for Space Research (INPE), Brazil, since 1988, and a full researcher since 2009. His work focuses on inverse problems, data assimilation, numerical methods and artificial neural networks.
Antônio José da Silva Neto holds a bachelor’s degree in Mechanical and Nuclear Engineering (1983) and a master’s degree in Nuclear Engineering (1989) from the Federal University of Rio de Janeiro, and a PhD in Mechanical Engineering from North Carolina State University (1993). He worked for the Brazilian National Nuclear Energy Commission (1984-1986), and Promon Engenharia (1986-1997). In 1997 he joined the Polytechnic Institute of Rio de Janeiro State University, where he has been a professor since 2013. His research interests are in two main areas: mechanical engineering, with a focus on heat transfer, and applied and computational mathematics, with a focus on numerical methods and inverse problems.

Table of contents (5 chapters)

Table of contents (5 chapters)
  • Model Based Fault Diagnosis and Inverse Problems

    Pages 1-9

    Camps Echevarría, Lídice (et al.)

  • Fault Diagnosis Inverse Problems

    Pages 11-41

    Camps Echevarría, Lídice (et al.)

  • Metaheuristics for Optimization Problems

    Pages 43-83

    Camps Echevarría, Lídice (et al.)

  • Applications of the Fault Diagnosis: Inverse Problem Methodology to Benchmark Problems

    Pages 85-138

    Camps Echevarría, Lídice (et al.)

  • Final Remarks

    Pages 139-140

    Camps Echevarría, Lídice (et al.)

Buy this book

eBook $84.99
price for USA in USD (gross)
  • ISBN 978-3-319-89978-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $109.99
price for USA in USD
  • ISBN 978-3-319-89977-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $109.99
price for USA in USD
  • ISBN 978-3-030-07908-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Fault Diagnosis Inverse Problems: Solution with Metaheuristics
Authors
Series Title
Studies in Computational Intelligence
Series Volume
763
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-89978-7
DOI
10.1007/978-3-319-89978-7
Hardcover ISBN
978-3-319-89977-0
Softcover ISBN
978-3-030-07908-6
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XVIII, 167
Number of Illustrations
16 b/w illustrations, 52 illustrations in colour
Topics