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.
Part I: Trends and Applications.- Chapter 1. Probabilistic Prognostics and Health Management: A Brief Summary.- Chapter 2. Introduction to Data-driven Methodologies for Prognostics and Health Management.- Chapter 3. Prognostics and Health Management of Wind Turbines Current Status and Future Opportunities.- Chapter 4. Overview on Gear Health Prognostics.- Chapter 5. Probabilistic Model-Based Prognostics Using Meshfree Modeling.- Chapter 6. Cognitive Architectures for Prognostic Health Management.- Part II Modeling and Uncertainty Quantification.- Chapter 7. A Review of Crack Propagation Modeling using Peridynamics.- Chapter 8. Modeling and Quantification of Physical Systems Uncertainties in a Probabilistic Framework.- Chapter 9. Towards a More Robust Understanding of the Uncertainty of Wind Farm Reliability.- Chapter 10. DalÓÎ
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