Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems - Couverture rigide

Yan, Ruqiang; Zhao, Zhibin

 
9781032752372: Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems
Couverture rigide
ISBN 10 : 1032752378 ISBN 13 : 9781032752372
Editeur : CRC Press, 2024

Synopsis

The book aims to highlight the potential of deep learning (DL)-enabled methods in intelligent fault diagnosis (IFD), along with their benefits and contributions.

The authors first introduce basic applications of DL-enabled IFD, including auto-encoders, deep belief networks, and convolutional neural networks. Advanced topics of DL-enabled IFD are also explored, such as data augmentation, multi-sensor fusion, unsupervised deep transfer learning, neural architecture search, self-supervised learning, and reinforcement learning. Aiming to revolutionize the nature of IFD, Deep Neural Networks-Enabled Intelligent Fault Diangosis of Mechanical Systems contributes to improved efficiency, safety, and reliability of mechanical systems in various industrial domains.

The book will appeal to academic researchers, practitioners, and students in the fields of intelligent fault diagnosis, prognostics and health management, and deep learning.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l?auteur

Ruqiang Yan is a professor at the School of Mechanical Engineering, Xi'an Jiaotong University. His research interests include data analytics, AI, and energy-efficient sensing and sensor networks for the condition monitoring and health diagnosis of large-scale, complex, dynamical systems.

Zhibin Zhao is an assistant professor at the School of Mechanical Engineering, Xi'an Jiaotong University. His research interests include sparse signal processing and machine learning, especially deep learning for machine fault detection, diagnosis, and prognosis.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
CRC Press
Date d'édition
2024
Langue
anglais
ISBN 10 
1032752378
ISBN 13 
9781032752372
Reliure
Relié
Nombre de pages
232
Coordonnées du fabricant
non disponible
Personne responsable
gpsr@libri.de
gpsr@libri.de

Friedensallee 273
Hamburg
22763
Allemagne

Autres éditions populaires du même titre

9781032757247: Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems

Edition présentée

ISBN 10 :  1032757248 ISBN 13 :  9781032757247
Editeur : CRC Press, 2026
Couverture souple