Probabilistic Prognostics and Health Management of Energy Systems [electronic resource] /
Ekwaro-Osire, Stephen.editor.
Gonçalves, Aparecido Carlos.editor.
Alemayehu, Fisseha M.editor.
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. Data Analysis in Python: Anonymized Features and Imbalanced Data Target -- Chapter 11. The Use of Trend Lines Channels and Remaining Useful Life Prediction. Chapter -- 12. The Derivative as a Probabilistic Synthesis of Past and Future Data and Remaining Useful Life Prediction -- Part III Condition Monitoring -- Chapter 13. Monitoring and Fault Identification in Aeronautical Structures Using an Wavelet-Artificial Immune System Algorithm -- Chapter 14. An Illustration of Some Methods to Detect Faults in Geared Systems using a Simple Model of Two Meshed Gears -- Chapter 15. Condition Monitoring of Structures under Non-Ideal Excitation using Low Cost Equipment -- Chapter 16. Maintenance Management and Case Studies in the Luís Carlos Prestes Thermoelectric Power Plant -- Chapter 17. Stiffness Nonlinearity in Structural Dynamics: Our Friend or Enemy?.
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.
Energy systems.
Quality control.
Reliability.
Industrial safety.
Computational intelligence.
Probabilities.
Thermodynamics.
Heat engineering.
Heat transfer.
Mass transfer.
Energy Systems.
Quality Control, Reliability, Safety and Risk.
Computational Intelligence.
Probability Theory and Stochastic Processes.
Engineering Thermodynamics, Heat and Mass Transfer.