Isbn: 9786209500664 - intelligent diagnosis of rotating machines using vmd: advanced approaches to signal processing and machine learning (11 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

Zustand: New.

Taschenbuch. Zustand: Neu. Intelligent diagnosis of rotating machines using VMD | Advanced approaches to signal processing and machine learning | Ammar Mrabti (u. a.) | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786209500664 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 120 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents an innovative approach to fault diagnosis in rotating machines, based on Variational Mode Decomposition (VMD) and artificial intelligence techniques. It begins with an analysis of condition monitoring strategies and the limitations of conventional signal processing methods. VMD is compared with Empirical Mode Decomposition (EMD) to demonstrate its superiority for extracting fault signatures in noisy environments. A criterion based on Shannon entropy is proposed to optimize the number of modes, while the integration of Multiresolution Wavelet Decomposition (WMRA) improves detection of weak defects. Finally, a hybrid VMD-LSTM model is developed for automatic classification and assessment of fault severity. Combining scientific rigor and experimental validation, this book offers a major contribution to predictive diagnostics and intelligent maintenance in the context of Industry 4.0.…

Paperback. Zustand: new. Paperback. This book presents an innovative approach to fault diagnosis in rotating machines, based on Variational Mode Decomposition (VMD) and artificial intelligence techniques. It begins with an analysis of condition monitoring strategies and the limitations of conventional signal processing methods. VMD is compared with Empirical Mode Decomposition (EMD) to demonstrate its superiority for extracting fault signatures in noisy environments. A criterion based on Shannon entropy is proposed to optimize the number of modes, while the integration of Multiresolution Wavelet Decomposition (WMRA) improves detection of weak defects. Finally, a hybrid VMD-LSTM model is developed for automatic classification and assessment of fault severity. Combining scientific rigor and experimental validation, this book offers a major contribution to predictive diagnostics and intelligent maintenance in the context of Industry 4.0. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Zustand: New. Print on Demand.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents an innovative approach to fault diagnosis in rotating machines, based on Variational Mode Decomposition (VMD) and artificial intelligence techniques. It begins with an analysis of condition monitoring strategies and the limitations of conventional signal processing methods. VMD is compared with Empirical Mode Decomposition (EMD) to demonstrate its superiority for extracting fault signatures in noisy environments. A criterion based on Shannon entropy is proposed to optimize the number of modes, while the integration of Multiresolution Wavelet Decomposition (WMRA) improves detection of weak defects. Finally, a hybrid VMD-LSTM model is developed for automatic classification and assessment of fault severity. Combining scientific rigor and experimental validation, this book offers a major contribution to predictive diagnostics and intelligent maintenance in the context of Industry 4.0.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch.…

Zustand: New. PRINT ON DEMAND.