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Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems (Hardcover, 1st ed. 2023): Yaguo Lei, Naipeng... Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems (Hardcover, 1st ed. 2023)
Yaguo Lei, Naipeng Li, Xiang Li
R3,185 Discovery Miles 31 850 Ships in 12 - 17 working days

This book presents systematic overviews and bright insights into big data-driven intelligent fault diagnosis and prognosis for mechanical systems. The recent research results on deep transfer learning-based fault diagnosis, data-model fusion remaining useful life (RUL) prediction, etc., are focused on in the book. The contents are valuable and interesting to attract academic researchers, practitioners, and students in the field of prognostics and health management (PHM). Essential guidelines are provided for readers to understand, explore, and implement the presented methodologies, which promote further development of PHM in the big data era. Features: Addresses the critical challenges in the field of PHM at present Presents both fundamental and cutting-edge research theories on intelligent fault diagnosis and prognosis Provides abundant experimental validations and engineering cases of the presented methodologies

Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery (Paperback, UK ed.): Yaguo Lei Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery (Paperback, UK ed.)
Yaguo Lei
R3,563 Discovery Miles 35 630 Ships in 12 - 17 working days

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.

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