Vibration Basics and Machine Reliability Simplified

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