000 | 06488cam a2200625 i 4500 | ||
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001 | on1043051822 | ||
003 | OCoLC | ||
005 | 20220711203537.0 | ||
006 | m o d | ||
007 | cr ||||||||||| | ||
008 | 180702s2018 nju ob 001 0 eng | ||
010 | _a 2018031572 | ||
040 |
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019 |
_a1048895928 _a1049605644 |
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_a9781119515357 _q(ePub) |
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020 | _a1119515351 | ||
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_a9781119515302 _q(Adobe PDF) |
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020 | _a1119515300 | ||
020 |
_a9781119515326 _q(electronic bk.) |
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_a1119515327 _q(electronic bk.) |
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_z9781119515333 _q(hardcover) |
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020 | _z1119515335 | ||
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_a(OCoLC)1043051822 _z(OCoLC)1048895928 _z(OCoLC)1049605644 |
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042 | _apcc | ||
050 | 1 | 0 | _aTK7870 |
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_aTEC _x009070 _2bisacsh |
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_a621.381028/8 _223 |
049 | _aMAIN | ||
245 | 0 | 0 |
_aPrognostics and health management of electronics : _bfundamentals, machine learning, and internet of things / _cedited by Michael Pecht, Ph. D., PE, Myeongsu Kang, Ph. D. |
250 | _aSecond edition. | ||
264 | 1 |
_aHoboken, NJ : _bJohn Wiley & Sons, _c2018. |
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300 | _a1 online resource | ||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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504 | _aIncludes bibliographical references and index. | ||
588 | 0 | _aPrint version record and CIP data provided by publisher. | |
505 | 0 | _aCover; 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. | |
505 | 8 | _a1.3.3.1 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. | |
505 | 8 | _a1.5.7 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. | |
505 | 8 | _a2.2.4.2 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. | |
505 | 8 | _a3.5 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. | |
520 | _aAN 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 all areas of electronics and explains how to: . assess methods for damage estimation of components and systems due to field loading conditions. assess the cost and benefits of prognostic implementations. develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions. enable condition-based "predictive" maintenance. increase system availability through an extension of maintenance cycles and/or timely repair actions. obtain knowledge of load history for future design, qualification, and root cause analysis. reduce the occurrence of no fault found "NFF". subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment. | ||
650 | 0 |
_aElectronic systems _xMaintenance and repair. _98642 |
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650 | 7 |
_aTECHNOLOGY & ENGINEERING _xMechanical. _2bisacsh _98643 |
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650 | 7 |
_aElectronic systems _xMaintenance and repair. _2fast _0(OCoLC)fst00907488 _98642 |
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655 | 0 |
_aElectronic books. _93294 |
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655 | 4 |
_aElectronic books. _93294 |
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700 | 1 |
_aPecht, Michael, _eeditor. _98644 |
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700 | 1 |
_aKang, Myeongsu, _d1980- _eeditor. _98645 |
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776 | 0 | 8 |
_iPrint version: _tPrognostics and health management of electronics. _bSecond edition. _dHoboken, NJ : John Wiley & Sons, 2018 _z9781119515333 _w(DLC) 2018029737 |
856 | 4 | 0 |
_uhttps://doi.org/10.1002/9781119515326 _zWiley Online Library |
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