Yan Ruqiang (99 results)

Condition: New.

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

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

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

Condition: As New. Unread book in perfect condition.

Condition: 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.

Condition: New.

Condition: New.

Condition: New.

Taschenbuch. Condition: 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.…

Condition: As New. Unread book in perfect condition.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: New. In English.

Condition: New. 1st edition NO-PA16APR2015-KAP.

Condition: New.

Condition: New.

Condition: New. In English.

Condition: New. In English.

Condition: New. In English.

Condition: New.

Paperback. Condition: new. Paperback. Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New. Softcover reprint of the original 1st ed. 2017 edition NO-PA16APR2015-KAP.

Condition: New. In English.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: Brand New. 232 pages. 10.00x7.00x10.00 inches. In Stock.

Taschenbuch. Condition: 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. Condition: 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.…

Taschenbuch. Condition: 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. …

Taschenbuch. Condition: 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. …

Condition: 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.…