Idioma: Inglés
Publicado por Springer Nature Switzerland AG, Cham, 2025
ISBN 10: 9819672171 ISBN 13: 9789819672172
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Añadir al carritoHardcover. Condición: new. Hardcover. This book gives a detailed introduction to the technical background, feature extraction methods, PHM models and big data embedding methods of the big data theory in PHM for intelligent electromechanical systems. Combination with deep learning and big data, this book explains the hybrid algorithm framework of PHM such as ensemble intelligence and optimized intelligence and introduces PHM models for bearing, IGBT, MOSFET and other components and their big data embedding platform. This book improves the PHM method and theory of electromechanical system under industrial big data and provides reference for the development of intelligent electromechanical equipment and intelligent industrial production in the future. This book gives a detailed introduction to the technical background, feature extraction methods, PHM models and big data embedding methods of the big data theory in PHM for intelligent electromechanical systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoHardcover. Condición: Brand New. 230 pages. 9.26x6.11x9.49 inches. In Stock.
Idioma: Inglés
Publicado por Springer Nature Singapore, Springer Jul 2025, 2025
ISBN 10: 9819672171 ISBN 13: 9789819672172
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: Neu. Neuware - This book gives a detailed introduction to the technical background, feature extraction methods, PHM models and big data embedding methods of the big data theory in PHM for intelligent electromechanical systems. Combination with deep learning and big data, this book explains the hybrid algorithm framework of PHM such as ensemble intelligence and optimized intelligence and introduces PHM models for bearing, IGBT, MOSFET and other components and their big data embedding platform. This book improves the PHM method and theory of electromechanical system under industrial big data and provides reference for the development of intelligent electromechanical equipment and intelligent industrial production in the future.
Idioma: Inglés
Publicado por Springer Nature Singapore, Springer Jul 2025, 2025
ISBN 10: 9819672171 ISBN 13: 9789819672172
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book gives a detailed introduction to the technical background, feature extraction methods, PHM models and big data embedding methods of the big data theory in PHM for intelligent electromechanical systems. Combination with deep learning and big data, this book explains the hybrid algorithm framework of PHM such as ensemble intelligence and optimized intelligence and introduces PHM models for bearing, IGBT, MOSFET and other components and their big data embedding platform. This book improves the PHM method and theory of electromechanical system under industrial big data and provides reference for the development of intelligent electromechanical equipment and intelligent industrial production in the future. 232 pp. Englisch.
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Añadir al carritoBuch. Condición: Neu. Prognostics and Health Management for Intelligent Electromechanical Systems | Hui Liu (u. a.) | Buch | xxi | Englisch | 2025 | Springer | EAN 9789819672172 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Idioma: Inglés
Publicado por Springer, Springer Jul 2025, 2025
ISBN 10: 9819672171 ISBN 13: 9789819672172
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book gives a detailed introduction to the technical background, feature extraction methods, PHM models and big data embedding methods of the big data theory in PHM for intelligent electromechanical systems. Combination with deep learning and big data, this book explains the hybrid algorithm framework of PHM such as ensemble intelligence and optimized intelligence and introduces PHM models for bearing, IGBT, MOSFET and other components and their big data embedding platform. This book improves the PHM method and theory of electromechanical system under industrial big data and provides reference for the development of intelligent electromechanical equipment and intelligent industrial production in the future.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 232 pp. Englisch.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 192,84
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