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[eBook Code] Intelligent Fault Diagnosis and Prognosis for Engineering Systems

[eBook Code] Intelligent Fault Diagnosis and Prognosis for Engineering Systems (eBook Code, 1st)

Frank L. Lewis, George Vachtsevanos, Michael Roemer, Andrew Hess, Biqing Wu (지은이)
  |  
Wiley
2008-05-02
  |  
272,370원

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[eBook Code] Intelligent Fault Diagnosis and Prognosis for Engineering Systems

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· 제목 : [eBook Code] Intelligent Fault Diagnosis and Prognosis for Engineering Systems (eBook Code, 1st) 
· 분류 : 외국도서 > 기술공학 > 기술공학 > 품질관리
· ISBN : 9780470361061
· 쪽수 : 456쪽

목차

PREFACE.

ACKNOWLEDGMENTS.

PROLOGUE.

1 INTRODUCTION.

1.1 Historical Perspective.

1.2 Diagnostic and Prognostic System Requirements.

1.3 Designing in Fault Diagnostic and Prognostic Systems.

1.4 Diagnostic and Prognostic Functional Layers.

1.5 Preface to Book Chapters.

1.6 References.

2 SYSTEMS APPROACH TO CBM/PHM.

2.1 Introduction.

2.2 Trade Studies.

2.3 Failure Modes and Effects Criticality Analysis (FMECA).

2.4 System CBM Test-Plan Design.

2.5 Performance Assessment.

2.6 CBM/PHM Impact on Maintenance and Operations: Case Studies.

2.7 CBM/PHM in Control and Contingency Management.

2.8 References.

3 SENSORS AND SENSING STRATEGIES.

3.1 Introduction.

3.2 Sensors.

3.3 Sensor Placement.

3.4 Wireless Sensor Networks.

3.5 Smart Sensors.

3.6 References.

4 SIGNAL PROCESSING AND DATABASE MANAGEMENT SYSTEMS.

4.1 Introduction.

4.2 Signal Processing in CBM/PHM.

4.3 Signal Preprocessing.

4.4 Signal Processing.

4.5 Vibration Monitoring and Data Analysis.

4.6 Real-Time Image Feature Extraction and Defect/Fault Classification.

4.7 The Virtual Sensor.

4.8 Fusion or Integration Technologies.

4.9 Usage-Pattern Tracking.

4.10 Database Management Methods.

4.11 References.

5 FAULT DIAGNOSIS.

5.1 Introduction.

5.2 The Diagnostic Framework.

5.3 Historical Data Diagnostic Methods.

5.4 Data-Driven Fault Classification and Decision Making.

5.5 Dynamic Systems Modeling.

5.6 Physical Model–Based Methods.

5.7 Model-Based Reasoning.

5.8 Case-Based Reasoning (CBR).

5.9 Other Methods for Fault Diagnosis.

5.10 A Diagnostic Framework for Electrical/Electronic Systems.

5.11 Case Study: Vibration-Based Fault Detection and Diagnosis for Engine Bearings.

5.12 References.

6 FAULT PROGNOSIS.

6.1 Introduction.

6.2 Model-Based Prognosis Techniques.

6.3 Probability-Based Prognosis Techniques.

6.4 Data-Driven Prediction Techniques.

6.5 Case Studies.

6.6 References.

7 FAULT DIAGNOSIS AND PROGNOSIS PERFORMANCE METRICS.

7.1 Introduction.

7.2 CBM/PHM Requirements Definition.

7.3 Feature-Evaluation Metrics.

7.4 Fault Diagnosis Performance Metrics.

7.5 Prognosis Performance Metrics.

7.6 Diagnosis and Prognosis Effectiveness Metrics.

7.7 Complexity/Cost-Benefit Analysis of CBM/PHM Systems.

7.8 References.

8 LOGISTICS: SUPPORT OF THE SYSTEM IN OPERATION.

8.1 Introduction.

8.2 Product-Support Architecture, Knowledge Base, and Methods for CBM.

8.3 Product Support without CBM.

8.4 Product Support with CBM.

8.5 Maintenance Scheduling Strategies.

8.6 A Simple Example.

8.7 References.

APPENDIX.

INDEX.

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