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Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Introduction -- 1. Diagnostic Methods for the Health Monitoring of Gearboxes -- 1.1. Introduction -- 1.2. Identification of critical components in gearboxes -- 1.2.1. Types of gears -- 1.2.2. Types of gear defects -- 1.3. Diagnostic methodology -- 1.4. Methods of analysis -- 1.4.1. Temperature analysis -- 1.4.2. Oil analysis -- 1.4.3. Acoustic analysis -- 1.4.4. Vibration analysis -- 1.4.5. Electromagnetic torque analysis -- 1.4.6. Flux analysis -- 1.4.7. Analysis of electric currents -- 1.5. Monitoring methods -- 1.5.1. Temporal analysis -- 1.5.2. Frequency analysis -- 1.5.3. Time-frequency analysis -- 1.6. Diagnostic methods -- 1.6.1. Model approach -- 1.6.2. Data-driven approach -- 1.7. Conclusion -- 1.8. References -- 2. Techniques for Predicting Defects in Bearings and Gears -- 2.1. Introduction -- 2.1.1. Bearing degradation -- 2.1.2. Degradation of gears -- 2.2. Prediction -- 2.2.1. Hidden Markov models -- 2.2.2. Fault prediction by identifying the degradation process of the system -- 2.3. Conclusion -- 2.4. References -- 3. Electrical Signatures Analysis for Condition Monitoring of Gears -- 3.1. Introduction -- 3.1.1. Different kinds of gear defects -- 3.1.2. Torsional vibration study -- 3.2. Gear torsional vibration effects on EMSs -- 3.3. Modeling gears in complex electromechanical systems -- 3.3.1. Parallel shaft gears -- 3.3.2. Planetary gears -- 3.3.3. Mechanical shafts and couplings -- 3.3.4. Electrical machine model -- 3.4. Modeling gear tooth surface damage faults -- 3.4.1. Parallel shaft gears -- 3.4.2. Planetary gear faults -- 3.5. Online condition monitoring of gears in complex electromechanical systems -- 3.5.1. Mechanical torque and stator current analysis -- 3.5.2. Stator current space vector analysis -- 3.6. Conclusion -- 3.7. References.