NA
Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems
Product Code:
9781032752372
ISBN13:
9781032752372
Condition:
New
$106.81
Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems
$106.81
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 revolutionise the nature of IFD, the book 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.
| Author: Ruqiang Yan, Zhibin Zhao |
| Publisher: NA |
| Publication Date: Jun 06, 2024 |
| Number of Pages: NA pages |
| Language: English |
| Binding: Hardcover |
| ISBN-10: 1032752378 |
| ISBN-13: 9781032752372 |
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