Fundamentals of Rotating Machinery Diagnostics 1st Edition by Donald Bently, Charles Hatch ISBN 0971408106 9780971408104

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ISBN 10: 0971408106
ISBN 13: 9780971408104
Author: Donald Bently, Charles Hatch

A practical course in the fundamentals of machinery diagnostics for anyone who works with rotating machinery, from operator to manager, from design engineer to machinery diagnostician. This comprehensive book thoroughly explains and demystifies important concepts needed for effective machinery malfunction diagnosis: (A) Vibration fundamentals: vibration, phase, and vibration vectors. (B) Data plots: timebase, average shaft centerline, polar, Bode, APHT, spectrum, trend XY, and the orbit. (C) Rotor dynamics: the rotor model, dynamic stiffness, modes of vibration, anisotropic (asymmetric) stiffness, stability analysis, torsional and axial vibration, and basic balancing. Modern root locus methods (pioneered by Walter R. Evans) are used throughout this book. (D) Malfunctions: unbalance, rotor bow, high radial loads, misalignment, rub and looseness, fluid-induced instability, and shaft cracks. Hundreds of full-color illustrations explain key concepts, and several detailed case studies show how these concepts were used to solve real machinery problems. A comprehensive glossary of diagnostic terms is included.

Fundamentals of Rotating Machinery Diagnostics 1st Edition Table of contents:

Part I: Introduction to Rotating Machinery

1. Overview of Rotating Machinery

   • Types of Rotating Machinery: Pumps, Compressors, Motors, Turbines, and Generators
   • Basic Operating Principles of Rotating Machinery
   • Common Failure Modes in Rotating Equipment
   • Importance of Diagnostics in Machinery Maintenance

2. Fundamentals of Vibration Analysis

   • Introduction to Vibration and its Role in Diagnostics
   • Vibration Characteristics and Parameters: Displacement, Velocity, and Acceleration
   • Frequency Analysis and Spectrum Representation
   • Overview of Vibration Measurement Tools and Equipment

3. Types of Rotating Machinery Failures

   • Mechanical Failures: Bearings, Shafts, Couplings, Gears, and Seals
   • Electrical Failures: Motor Stator, Rotor, and Electrical Insulation
   • Thermal Failures: Overheating and Heat Generation
   • Fluid Dynamic Failures: Cavitation, Imbalance, and Misalignment

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Part II: Diagnostic Techniques

4. Condition Monitoring Methods

   • Introduction to Condition Monitoring for Rotating Machinery
   • Vibration Monitoring and Analysis
   • Temperature Monitoring and Infrared Thermography
   • Oil Analysis and Tribology Techniques
   • Acoustic Emission and Ultrasonic Testing

5. Vibration Diagnostics and Signature Analysis

   • Identifying Faults Through Vibration Signature Analysis
   • Modal Analysis and Frequency Domain Methods
   • Time Domain and Statistical Methods
   • Bearing and Gearbox Fault Detection through Vibration Analysis
   • Rotor Dynamics and Imbalance Detection

6. Thermographic Diagnostics

   • Principles of Infrared Thermography
   • Identifying Hotspots and Thermal Anomalies
   • Applications in Motor and Bearing Monitoring
   • Thermographic Data Interpretation and Reporting

7. Oil Analysis and Lubrication Diagnostics

   • Role of Lubrication in Rotating Machinery
   • Common Oil Contaminants and Their Significance
   • Particle Count and Wear Debris Analysis
   • Viscosity, Additive Depletion, and Oil Condition Monitoring
   • Integrating Oil Analysis with Vibration Data for Fault Detection

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Part III: Advanced Diagnostics and Analysis

8. Advanced Vibration Analysis Techniques

   • Advanced Time-Frequency Analysis: Wavelets and Short-Time Fourier Transform
   • Envelope Analysis and Demodulation for Bearing Faults
   • Sideband Analysis and Harmonic Diagnosis
   • Multi-Channel Vibration Data Acquisition and Analysis
   • Fault Diagnosis Using Modal and Operational Deflection Shape Analysis

9. Signal Processing and Data Interpretation

   • Digital Signal Processing (DSP) Methods in Diagnostics
   • Filtering and Noise Reduction Techniques
   • Data Acquisition Systems for Rotating Machinery Monitoring
   • Diagnostic Software and Automated Analysis Tools
   • Developing Fault Detection Algorithms and Decision Support Systems

10. Integrated Monitoring Systems

    • The Role of SCADA (Supervisory Control and Data Acquisition) Systems
    • Condition Monitoring Networks and Data Integration
    • Predictive Maintenance and Reliability-Centered Maintenance (RCM)
    • Real-Time Monitoring and Prognostics for Rotating Machinery

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Part IV: Applications and Case Studies

11. Applications in Industrial Equipment

    • Diagnostic Techniques for Pumps and Compressors
    • Vibration and Thermal Monitoring of Motors and Fans
    • Diagnostics for Steam and Gas Turbines
    • Monitoring Large Rotating Machinery in Power Generation

12. Case Studies in Rotating Machinery Diagnostics

    • Case Study 1: Bearing Failure Detection in a Pump System
    • Case Study 2: Shaft Imbalance and Misalignment in a Compressor
    • Case Study 3: Vibration Analysis for Gearbox Diagnostics
    • Case Study 4: Predicting Rotor Failures in a Gas Turbine
    • Case Study 5: Application of Thermography in Motor Maintenance

13. Root Cause Analysis and Troubleshooting

    • Methods for Root Cause Analysis (RCA)
    • Investigation Process for Machinery Failures
    • Integrating Diagnostics Data for Effective Problem Solving
    • Troubleshooting Strategies for Common Rotating Machinery Issues

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Part V: Maintenance Strategies

14. Condition-Based Maintenance (CBM) and Predictive Maintenance

    • Introduction to CBM and its Role in Modern Maintenance Strategies
    • Developing Predictive Maintenance Programs
    • The Role of Diagnostics in Reducing Unscheduled Downtime
    • Cost-Benefit Analysis of Predictive Maintenance Programs

15. Reliability-Centered Maintenance (RCM) for Rotating Machinery

    • Principles of Reliability-Centered Maintenance
    • Identifying Critical Machinery and Failure Modes
    • Building Effective RCM Strategies Using Diagnostic Data
    • Maintenance Planning and Optimization Using Diagnostics

16. Maintenance Optimization and Life Cycle Management

    • Integrating Diagnostics into Maintenance Decision Making
    • Predicting Remaining Useful Life (RUL) of Rotating Machinery
    • Life Cycle Cost Analysis for Rotating Equipment
    • Performance Monitoring and Continuous Improvement

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Part VI: Future Trends and Emerging Technologies

17. Emerging Technologies in Rotating Machinery Diagnostics

    • The Role of Artificial Intelligence (AI) and Machine Learning in Diagnostics
    • Big Data and the Internet of Things (IoT) for Equipment Monitoring
    • Remote Monitoring and Cloud-Based Diagnostic Platforms
    • Advancements in Wireless Sensors and Smart Machinery

18. Future Trends in Rotating Machinery Maintenance

    • The Evolution of Predictive Maintenance Technologies
    • Digital Twins and Virtual Modeling for Machinery Health Monitoring
    • Autonomous Diagnostics and Self-Healing Systems
    • Challenges and Opportunities in Rotating Machinery Diagnostics

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