Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems (Hardcover, 1st ed. 2023)

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

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	October 2022
First published:	2023
Authors:	Yaguo Lei • Naipeng Li • Xiang Li
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	281
Edition:	1st ed. 2023
ISBN-13:	978-981-16-9130-0
Languages:	English
Subtitles:	English
Categories:	Books > Professional & Technical > Mechanical engineering & materials > Mechanical engineering > Engines & power transmission > General
LSN:	981-16-9130-4
Barcode:	9789811691300

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