Probabilistic Prognostics and Health Management of Energy Systems
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Beschreibung
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.
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.
Contains chapters considering engineering, reliability, prognostics and health management, probabilistic multibody dynamical analysis, peridynamic and finite-element modelling, computer science, and mathematics Proposes a methodology that estimates system uncertainty and predicts Remaining Useful Life (RUL) efficiently and with greater accuracy Includes case studies, illustrations, graphs, and charts Surveys existing and novel ideas that will be implemented in RUL prediction of energy systems Includes supplementary material: sn.pub/extras
Autor*in
Stephen Ekwaro-Osire
Themen in »Probabilistic Prognostics and Health Management of Energy Systems«
Model-based Prognostics Uncertainty Quantification Energy Reliability Remaining Useful Life RUL prediction PHM research System Health Management quality control, reliability, safety and risk