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Prognostics and health management of electronics : fundamentals, machine learning, and internet of things /
AN INDISPENSABLE GUIDE FOR ENGINEERS AND DATA SCIENTISTS IN DESIGN, TESTING, OPERATION, MANUFACTURING, AND MAINTENANCE A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management "PHM", this important work covers al...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ :
John Wiley & Sons,
2018.
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| Edición: | Second edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Title Page; Copyright; About the Editors; Contents; List of Contributors; Preface; About the Contributors; Acknowledgment; List of Abbreviations; Chapter 1 Introduction to PHM; 1.1 Reliability and Prognostics; 1.2 PHM for Electronics; 1.3 PHM Approaches; 1.3.1 PoF-Based Approach; 1.3.1.1 Failure Modes, Mechanisms, and Effects Analysis (FMMEA); 1.3.1.2 Life-Cycle Load Monitoring; 1.3.1.3 Data Reduction and Load Feature Extraction; 1.3.1.4 Data Assessment and Remaining Life Calculation; 1.3.1.5 Uncertainty Implementation and Assessment; 1.3.2 Canaries; 1.3.3 Data-Driven Approach.
- 1.3.3.1 Monitoring and Reasoning of Failure Precursors1.3.3.2 Data Analytics and Machine Learning; 1.3.4 Fusion Approach; 1.4 Implementation of PHM in a System of Systems; 1.5 PHM in the Internet of Things (IoT) Era; 1.5.1 IoT-Enabled PHM Applications: Manufacturing; 1.5.2 IoT-Enabled PHM Applications: Energy Generation; 1.5.3 IoT-Enabled PHM Applications: Transportation and Logistics; 1.5.4 IoT-Enabled PHM Applications: Automobiles; 1.5.5 IoT-Enabled PHM Applications: Medical Consumer Products; 1.5.6 IoT-Enabled PHM Applications: Warranty Services.
- 1.5.7 IoT-Enabled PHM Applications: Robotics1.6 Summary; References; Chapter 2 Sensor Systems for PHM; 2.1 Sensor and Sensing Principles; 2.1.1 Thermal Sensors; 2.1.2 Electrical Sensors; 2.1.3 Mechanical Sensors; 2.1.4 Chemical Sensors; 2.1.5 Humidity Sensors; 2.1.6 Biosensors; 2.1.7 Optical Sensors; 2.1.8 Magnetic Sensors; 2.2 Sensor Systems for PHM; 2.2.1 Parameters to be Monitored; 2.2.2 Sensor System Performance; 2.2.3 Physical Attributes of Sensor Systems; 2.2.4 Functional Attributes of Sensor Systems; 2.2.4.1 Onboard Power and Power Management.
- 2.2.4.2 Onboard Memory and Memory Management2.2.4.3 Programmable Sampling Mode and Sampling Rate; 2.2.4.4 Signal Processing Software; 2.2.4.5 Fast and Convenient Data Transmission; 2.2.5 Reliability; 2.2.6 Availability; 2.2.7 Cost; 2.3 Sensor Selection; 2.4 Examples of Sensor Systems for PHM Implementation; 2.5 Emerging Trends in Sensor Technology for PHM; References; Chapter 3 Physics-of-Failure Approach to PHM; 3.1 PoF-Based PHM Methodology; 3.2 Hardware Configuration; 3.3 Loads; 3.4 Failure Modes, Mechanisms, and Effects Analysis (FMMEA); 3.4.1 Examples of FMMEA for Electronic Devices.
- 3.5 Stress Analysis3.6 Reliability Assessment and Remaining-Life Predictions; 3.7 Outputs from PoF-Based PHM; 3.8 Caution and Concerns in the Use of PoF-Based PHM; 3.9 Combining PoF with Data-Driven Prognosis; References; Chapter 4 Machine Learning: Fundamentals; 4.1 Types of Machine Learning; 4.1.1 Supervised, Unsupervised, Semi-Supervised, and Reinforcement Learning; 4.1.2 Batch and Online Learning; 4.1.3 Instance-Based and Model-Based Learning; 4.2 Probability Theory in Machine Learning: Fundamentals; 4.2.1 Probability Space and Random Variables.