This edition transforms the classic guide into a complete modern reference for anyone involved in machinery health, reliability engineering, and predictive maintenance.This book walks you from the core principles of vibration analysis to advanced AI-powered fault detection. The result is a clear, practical, and future-ready approach to keeping machines running at peak performance.Inside:AI Integration: How machine learning can detect faults weeks before failure.Real-world examples from pumps, motors, gearboxes, and rotating equipment.Updated Methods: Digital twins, motion amplification, ultrasonic detection, and MCSA.Expanded Fault Coverage: From unbalance and misalignment to looseness, electrical defects, and rotor eccentricity.Foundation to Future: Bridging traditional techniques with Industry 4.0 predictive tools.Key Topics:Fundamentals of vibration analysis and machine dynamicsCommon fault types and their signaturesData collection, sensor placement, and interpretation techniquesPractical corrective actions to eliminate root causesBest practices for a sustainable condition monitoring programAI-based workflows for automated diagnostics and RUL prediction
