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Prognostics and Health Management : a Practical Approach to Improving System Reliability Using Condition-Based Data.
A comprehensive guide to the application and processing of condition-based data to produce prognostic estimates of functional health and life. Prognostics and Health Management provides an authoritative guide for an understanding of the rationale and methodologies of a practical approach for improvi...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Newark :
John Wiley & Sons, Incorporated,
2019.
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| Colección: | Quality and Reliability Engineering Ser.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Title Page; Copyright; Contents; List of Figures; Series Editor's Foreword; Preface; Acknowledgments; Chapter 1 Introduction to Prognostics; 1.1 What Is Prognostics?; 1.1.1 Chapter Objectives; 1.1.2 Chapter Organization; 1.2 Foundation of Reliability Theory; 1.2.1 Time-to-Failure Distributions; 1.2.2 Probability and Reliability; 1.2.3 Probability Density Function; 1.2.4 Relationships of Distributions; 1.2.5 Failure Rate; 1.2.6 Expected Value and Variance; 1.3 Failure Distributions Under Extreme Stress Levels; 1.3.1 Basic Models; 1.3.2 Cumulative Damage Models
- 1.3.3 General Exponential Models1.4 Uncertainty Measures in Parameter Estimation; 1.5 Expected Number of Failures; 1.5.1 Minimal Repair; 1.5.2 Failure Replacement; 1.5.3 Decreased Number of Failures Due to Partial Repairs; 1.5.4 Decreased Age Due to Partial Repairs; 1.6 System Reliability and Prognosis and Health Management; 1.6.1 General Framework for a CBM-Based PHM System; 1.6.2 Relationship of PHM to System Reliability; 1.6.3 Degradation Progression Signature (DPS) and Prognostics; 1.6.4 Ideal Functional Failure Signature (FFS) and Prognostics; 1.6.5 Non-ideal FFS and Prognostics
- Chapter 2 Approaches for Prognosis and Health Management/Monitoring (PHM)2.1 Introduction to Approaches for Prognosis and Health Management/Monitoring (PHM); 2.1.1 Model-Based Prognostic Approaches; 2.1.2 Data-Driven Prognostic Approaches; 2.1.3 Hybrid Prognostic Approaches; 2.1.4 Chapter Objectives; 2.1.5 Chapter Organization; 2.2 Model-Based Prognostics; 2.2.1 Analytical Modeling; 2.2.2 Distribution Modeling; 2.2.3 Physics of Failure (PoF) and Reliability Modeling; 2.2.4 Acceleration Factor (AF); 2.2.5 Complexity Related to Reliability Modeling; 2.2.6 Failure Distribution
- 2.2.7 Multiple Modes of Failure: Failure Rate and FIT2.2.8 Advantages and Disadvantages of Model-Based Prognostics; 2.3 Data-Driven Prognostics; 2.3.1 Statistical Methods; 2.3.2 Machine Learning (ML): Classification and Clustering; 2.4 Hybrid-Driven Prognostics; 2.5 An Approach to Condition-Based Maintenance (CBM); 2.5.1 Modeling of Condition-Based Data (CBD) Signatures; 2.5.2 Comparison of Methodologies: Life Consumption and CBD Signature; 2.5.3 CBD-Signature Modeling: An Illustration; 2.6 Approaches to PHM: Summary; References; Further Reading; Chapter 3 Failure Progression Signatures