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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 dynamics Common fault types and their signatures Data collection, sensor placement, and interpretation techniques Practical corrective actions to eliminate root causes Best practices for a sustainable condition monitoring program AI-based workflows for automated diagnostics and RUL prediction

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