Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery

Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery provides a comprehensive introduction of intelligent fault diagnosis and RUL prediction based on the current achievements of the author's research group. The main contents include multi-domain signal processing and feature extraction, intelligent diagnosis models, clustering algorithms, hybrid intelligent diagnosis strategies, and RUL prediction approaches, etc.

This book presents fundamental theories and advanced methods of identifying the occurrence, locations, and degrees of faults, and also includes information on how to predict the RUL of rotating machinery. Besides experimental demonstrations, many application cases are presented and illustrated to test the methods mentioned in the book.

This valuable reference provides an essential guide on machinery fault diagnosis that helps readers understand basic concepts and fundamental theories. Academic researchers with mechanical engineering or computer science backgrounds, and engineers or practitioners who are in charge of machine safety, operation, and maintenance will find this book very useful.

Provides a detailed background and roadmap of intelligent diagnosis and RUL prediction of rotating machinery, involving fault mechanisms, vibration characteristics, health indicators, and diagnosis and prognosticsPresents basic theories, advanced methods, and the latest contributions in the field of intelligent fault diagnosis and RUL predictionIncludes numerous application cases, and the methods, algorithms, and models introduced in the book are demonstrated by industrial experiences

1. Introduction and background 2. Signal Processing and feature extraction 3. Individual intelligent techniques based fault diagnosis 4. Clustering algorithms based fault diagnosis 5. Multidimensional hybrid intelligent diagnosis 6. RUL prediction