Probabilistic Prognostics and Health Management of Energy Systems

  • Stephen Ekwaro-Osire
  • Aparecido Carlos Gonçalves
  • Fisseha M. Alemayehu

Table of contents

  1. Front Matter
    Pages i-x
  2. Trends and Applications

    1. Front Matter
      Pages 1-1
    2. Fisseha M. Alemayehu, Stephen Ekwaro-Osire
      Pages 3-7
    3. Jay Lee, Chao Jin, Zongchang Liu, Hossein Davari Ardakani
      Pages 9-32
    4. Fuqiong Zhao, Zhigang Tian, Yong Zeng
      Pages 49-65
    5. Stephen Ekwaro-Osire, Haileyesus Belay Endeshaw, Fisseha M. Alemayehu, Ozhan Gecgel
      Pages 67-90
    6. James A. Crowder, John N. Carbone
      Pages 91-107
  3. Modeling and Uncertainty Quantification

    1. Front Matter
      Pages 109-109
    2. João Paulo Dias, Márcio Antonio Bazani, Amarildo Tabone Paschoalini, Luciano Barbanti
      Pages 111-126
    3. Carsten H. Westergaard, Shawn B. Martin, Jonathan R. White, Charles M. Carter, Benjamin Karlson
      Pages 157-167
    4. Luciano Barbanti, Berenice Camargo Damasceno, Aparecido Carlos Gonçalves, Hadamez Kuzminskas
      Pages 189-194
    5. Berenice Camargo Damasceno, Luciano Barbanti, Hadamez Kuzminskas, Márcio Antonio Bazani
      Pages 195-199
  4. Condition Monitoring

    1. Front Matter
      Pages 201-201
    2. Fernando P. A. Lima, Fábio R. Chavarette, Simone S. F. Souza, Mara L. M. Lopes
      Pages 203-219
    3. Fabrício Cesar Lobato de Almeida, Aparecido Carlos Gonçalves, Michael John Brennan, Amarildo T. Paschoalini, A. Arato Junior, Erickson F. M. Silva
      Pages 221-239
    4. Paulo J. Paupitz Gonçalves, Marcos Silveira
      Pages 241-261
    5. Bernardo Botamede, Leonardo Leucas, Marcelo Pelegrini
      Pages 263-269

About this book


This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty. 

Renewable and non-renewable sources of energy are being used to supply the demands of societies worldwide. These sources are mainly thermo-chemo-electro-mechanical systems that are subject to uncertainty in future loading conditions, material properties, process noise, and other design parameters.It book informs the reader of existing and new ideas that will be implemented in RUL prediction of energy systems in the future. 

The book provides case studies, illustrations, graphs, and charts. Its chapters consider engineering, reliability, prognostics and health management, probabilistic multibody dynamical analysis, peridynamic and finite-element modelling, computer science, and mathematics.


Model-based Prognostics Uncertainty Quantification Energy Reliability Remaining Useful Life RUL prediction PHM research System Health Management

Editors and affiliations

  • Stephen Ekwaro-Osire
    • 1
  • Aparecido Carlos Gonçalves
    • 2
  • Fisseha M. Alemayehu
    • 3
  1. 1.Department of Mechanical EngineeringTexas Tech University LubbockUSA
  2. 2.Faculdade de Engenharia de Ilha SolteiraUniversidade Estadual Paulista Centro, Ilha SolteiraBrazil
  3. 3.School of Engineering and Computer Science and MathematicsWest Texas A&M UniversityCanyonUSA

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Energy Energy (R0)
  • Print ISBN 978-3-319-55851-6
  • Online ISBN 978-3-319-55852-3
  • Buy this book on publisher's site
Industry Sectors
Chemical Manufacturing
Energy, Utilities & Environment
Oil, Gas & Geosciences