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portada Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems
Type
Physical Book
Author
Publisher
Language
English
Pages
281
Format
Paperback
Dimensions
23.4 x 15.6 x 1.6 cm
Weight
0.42 kg.
ISBN13
9789811691331
Categories

Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems

Yaguo Lei (Author) · Naipeng Li (Author) · Xiang Li (Author) · Springer · Paperback

Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems - Lei, Yaguo ; Li, Naipeng ; Li, Xiang

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Synopsis "Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems"

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 presentPresents both fundamental and cutting-edge research theories on intelligent fault diagnosis and prognosisProvides abundant experimental validations and engineering cases of the presented methodologies

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