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Více informací o knize Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems

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Anotace knihy

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

Parametry knihy

Zařazení knihy Knihy v angličtině Technology, engineering, agriculture Mechanical engineering & materials Mechanical engineering

• Plný název: Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems
• Autor: Yaguo Lei, Naipeng Li, Xiang Li
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 281
• EAN: 9789811691300
• ID: 38573861
• Nakladatelství: Springer, Berlin
• Hmotnost: 612 g
• Rozměry: 235 × 155 × 22 mm
• Rok vydání: 2022

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