Probabilistic prognostics and health management of energy systems

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

doi:10.1007/978-3-319-55852-3

Probabilistic prognostics and health management of energy systems

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

Mechanical Engineering

Research output: Book/Report › Book › peer-review

16 Scopus citations

Abstract

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.

Original language	English
Publisher	Springer International Publishing
Number of pages	277
ISBN (Electronic)	9783319558523
ISBN (Print)	9783319558516
DOIs	https://doi.org/10.1007/978-3-319-55852-3
State	Published - Apr 25 2017

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AB - 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.

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Probabilistic prognostics and health management of energy systems

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