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Probabilistic Prognostics and Health Management of Energy Systems

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Cover of 'Probabilistic Prognostics and Health Management of Energy Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Probabilistic Prognostics and Health Management: A Brief Summary
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    Chapter 2 Introduction to Data-Driven Methodologies for Prognostics and Health Management
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    Chapter 3 Prognostics and Health Management of Wind Turbines—Current Status and Future Opportunities
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    Chapter 4 Overview on Gear Health Prognostics
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    Chapter 5 Probabilistic Model-Based Prognostics Using Meshfree Modeling
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    Chapter 6 Cognitive Architectures for Prognostic Health Management
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    Chapter 7 A Review of Crack Propagation Modeling Using Peridynamics
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    Chapter 8 Modeling and Quantification of Physical Systems Uncertainties in a Probabilistic Framework
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    Chapter 9 Towards a More Robust Understanding of the Uncertainty of Wind Farm Reliability
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    Chapter 10 Data Analysis in Python: Anonymized Features and Imbalanced Data Target
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    Chapter 11 The Use of Trend Lines Channels and Remaining Useful Life Prediction
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    Chapter 12 The Derivative as a Probabilistic Synthesis of Past and Future Data and Remaining Useful Life Prediction
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    Chapter 13 Monitoring and Fault Identification in Aeronautical Structures Using an Wavelet-Artificial Immune System Algorithm
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    Chapter 14 An Illustration of Some Methods to Detect Faults in Geared Systems Using a Simple Model of Two Meshed Gears
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    Chapter 15 Condition Monitoring of Structures Under Non-ideal Excitation Using Low Cost Equipment
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    Chapter 16 Maintenance Management and Case Studies in the Luís Carlos Prestes Thermoelectric Power Plant
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    Chapter 17 Stiffness Nonlinearity in Structural Dynamics: Our Friend or Enemy?
Attention for Chapter 3: Prognostics and Health Management of Wind Turbines—Current Status and Future Opportunities
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Chapter title
Prognostics and Health Management of Wind Turbines—Current Status and Future Opportunities
Chapter number 3
Book title
Probabilistic Prognostics and Health Management of Energy Systems
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-55852-3_3
Book ISBNs
978-3-31-955851-6, 978-3-31-955852-3
Authors

Shuangwen Sheng, Sheng, Shuangwen

Editors

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

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 44%
Researcher 4 25%
Professor 1 6%
Lecturer 1 6%
Unknown 3 19%
Readers by discipline Count As %
Engineering 7 44%
Energy 3 19%
Computer Science 1 6%
Unknown 5 31%