Ruqiang yan (29 Ergebnisse)

Paperback. Zustand: Brand New. 206 pages. 7.01x0.49x10.00 inches. In Stock.

Zustand: New. 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.

Zustand: New.

Taschenbuch. Zustand: Neu. Neuware - 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.…

Zustand: As New. Unread book in perfect condition.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Structural Health Monitoring | An Advanced Signal Processing Perspective | Ruqiang Yan (u. a.) | Taschenbuch | Smart Sensors, Measurement and Instrumentation | xi | Englisch | 2018 | Springer | EAN 9783319858326 | 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. 232 pages. 10.00x7.00x10.00 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.…

Zustand: New. Provides a comprehensive survey on wavelets specifically related to problems encountered in manufacturingCovers the similarities and differences between wavelet transform and other analytical techniques commonly used on the factory floor for signal processi.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 388 | Sprache: Englisch | Produktart: Bücher | This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.…

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 388 | Sprache: Englisch | Produktart: Bücher | This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.…

Zustand: As New. Unread book in perfect condition.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Based on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice. …

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Based on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice.…

Zustand: New. Offers case studies for each transfer learning algorithm Optimizes the transfer learning models to solve specific engineering problems Describes the roles of transfer components, transfer fields, and transfer order in intelligent .

Hardcover. Zustand: Brand New. 388 pages. 9.25x6.10x0.98 inches. In Stock.

Hardcover. Zustand: Brand New. 478 pages. 9.25x6.10x1.14 inches. In Stock.

Paperback. Zustand: Brand New. 300 pages. 9.00x6.00x0.75 inches. In Stock.

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Hardcover. Zustand: gut. 2023. Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems In deutscher Sprache. pages.

Zustand: New.

Zustand: New. 2023. paperback. . . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - The proceedings of the First International Conference on Equipment Intelligent Operation and Maintenance (ICEIOM 2023) offer invaluable insights into the processes that ensure safe and reliable operation of equipment and guarantee the improvement of product life cycles.The book touches upon a wide array of topics including equipment condition monitoring, fault diagnosis, and remaining useful life prediction. With special emphasis on the integration of big data and machine learning, the papers contained in this publication highlight how these technologies make the equipment operation process highly automated and ingenious. Intelligent operation and maintenance is set to act as the driving force behind a new generation of smart manufacturing and equipment upgradation, and promote demand for intelligent product services and management.This is a highly beneficial guide to students, researchers, working professionals and enthusiasts who wish to stay updated on innovative research contributions and practical applications of state-of-the-art technologies in equipment operation and maintenance.…

Hardcover. Zustand: Brand New. 874 pages. 9.69x6.88x9.61 inches. In Stock.

Zustand: As New. Unread book in perfect condition.