Intelligent Machinery Fault Diagnostics and Prognostics

Intelligent Machinery Fault Diagnostics and Prognostics

The Future of Smart Manufacturing

Sharma, Ankit; Abou Houran, Mohamad; Goyal, Deepam

Taylor & Francis Ltd

05/2025

270

Dura

Inglês

9781032769479

Pré-lançamento - envio 15 a 20 dias após a sua edição

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1. Introduction to Fault Diagnostics and Prognostics: Direction Towards Smart Manufacturing 2. Advanced Diagnostics and Prognostics of Gearbox Faults in Smart Manufacturing: The Critical Role of Gearboxes 3. Vibration and Support Vector Machine-Based Fault Diagnosis of Bevel Gearbox 4. Identifying Inner-Race Fault of a Bearing Using Nonlinear Mode Decomposition Technique Supported by Blind Source Separation Methods 5. Detection and Classification of Low-Severity Stator Inter-Turn Faults in Induction Motors Using Temporal Features: A Comparative Machine Learning Approach 6. Feature Selection for Accurate Remaining Useful Life Prediction of Bearing Using Machine Learning 7. Deep Learning and Statistical Model-Based Data-Driven Intelligent Fault Prognostics of Rotary Machinery 8. Remaining Useful Life Prediction for Aircraft Structure: Towards a Digital Twin Ecosystem 9. Free Vibration Control of Crack Curved Cracked Simple Supported Beams using Fuzzy Logic Control with Particle Swarm Optimization Tuning 10. Fault Diagnosis of Composite Mono Leaf Spring based on Vibration Characteristics 11. Current Sensor Fault Tolerant Control for Model Predictive Control of Induction Motor Drives
Condition Monitoring;Maintenance;Sensors;Vibrations Signals;Machine Learning,;Signal Processing