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Zustand: New. In English.

Zustand: New. In English.

Zustand: New. pp. 480.

Taschenbuch. Zustand: Neu. Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems | Yaguo Lei (u. a.) | Taschenbuch | xiii | Englisch | 2023 | Springer | EAN 9789811691331 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Hardcover. Zustand: Brand New. 294 pages. 9.25x6.10x0.91 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery | Yaguo Lei | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2016 | Elsevier Inc | EAN 9780128115343 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Kartoniert / Broschiert. Zustand: New. 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 prognostics Presents basic theories, .

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is an open access publication. This book presents innovative strategies and cutting-edge research at the intersection of mechanical engineering and simulation technologies. Aimed at addressing the current challenges and limitations in mechanical design, this book presents an array of advanced methodologies and tools that promise to revolutionize the field. From integrating artificial intelligence and machine learning for design optimization to leveraging the latest in finite element analysis for enhanced stress modelling, the proceedings highlight the pivotal role of simulation in pushing the boundaries of what is possible in mechanical design. With a strong emphasis on sustainable design practices and the utilization of additive manufacturing, this collection not only serves as an indispensable resource for engineers, researchers, and students but also marks a significant step forward in bridging the gap between traditional mechanical design principles and modern computational innovations.

Paperback. Zustand: Brand New. 294 pages. 9.25x6.10x0.62 inches. In Stock.