Guangrui Wen (19 results)

Hardcover. Condition: Brand New. 366 pages. 9.25x6.10x9.49 inches. In Stock.

Hardcover. Condition: new. Hardcover. The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance.This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools.The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance. The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: Brand New. 210 pages. 9.25x6.10x9.49 inches. In Stock.

Condition: New. 2024th edition NO-PA16APR2015-KAP.

Taschenbuch. Condition: Neu. New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques | Advanced Machine Learning Models, Methods and Applications | Guangrui Wen (u. a.) | Taschenbuch | Smart Sensors, Measurement and Instrumentation | xvii | Englisch | 2025 | Springer | EAN 9789819711789 | 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 - The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance.This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools.The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance.This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools.The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance.

Hardcover. Condition: new. Hardcover. The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance.This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools.The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance. The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Condition: New. Print on Demand.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people s lives and proper.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance.This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools.The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance. 368 pp. Englisch.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance.This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools.The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance. 368 pp. Englisch.

Buch. Condition: Neu. New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques | Advanced Machine Learning Models, Methods and Applications | Guangrui Wen (u. a.) | Buch | Smart Sensors, Measurement and Instrumentation | xvii | Englisch | 2024 | Springer | EAN 9789819711758 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Condition: New. Print on Demand.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 368 pp. Englisch.

Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance.This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools.The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 368 pp. Englisch.

Condition: New. PRINT ON DEMAND.