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Digital Twin Technology in Condition Monitoring of Wind Turbines - Hardcover

Nkosinathi, Madushele; Obafemi, Olatunji; Paul, Adedeji

 
9781032250175: Digital Twin Technology in Condition Monitoring of Wind Turbines
Hardcover
ISBN 10: 1032250178 ISBN 13: 9781032250175
Verlag: CRC Press, 2026

Inhaltsangabe

This book discusses the application of digital twin (DT) in condition monitoring of offshore and onshore wind turbines, including a pertinent framework to explain critical component Condition Monitoring and Fault Diagnosis. Frequently used tools and enabling technologies for DT are briefly discussed while the associated benefits and challenges are analyzed. It identifies the key issues which need to be addressed in the wind energy industry to optimally benefit from DT.

Features:

  • Exclusive title on application of DT in wind turbine condition monitoring       
  • Develops DT framework for condition monitoring of wind turbine
  • Discusses industrial applications by wind turbine manufacturers and operators as case studies
  • Explores the interface between DT technology and condition monitoring
  • Extensively profiles recommendations for future research

This book is aimed at researchers and professionals in mechanical engineering, plant maintenance, wind engineering, and condition monitoring.

 

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Über die Autorin bzw. den Autor

Nkosinathi Madushele is a professional engineer registered with ECSA and holds a D.Eng. in Mechanical Engineering from the University of Johannesburg. He has industry and academic experience, having worked as a Junior Project Manager in construction and a Systems Engineer at ESKOM. He is currently the Head of the Department of Mechanical Engineering Science at the University of Johannesburg.

Obafemi O. Olatunji is a registered engineer, certified energy manager, and certified renewable energy professional with the Association of Energy Engineers. He holds a PhD in Mechanical Engineering focused on AI integration in energy systems. With ten years of experience in academia and industry, he is currently a program manager at UJ-PEETS, leading the energy and energy efficiency portfolio.

Paul A. Adedeji is an energy specialist at UJ-PEETS, focusing on AI and machine learning applications in renewable energy for resource prediction and condition monitoring. He holds a BSc. in Mechanical Engineering, MSc. in Industrial and Production Engineering, and a PhD. in Mechanical Engineering. He has published extensively on AI in wind and solar PV systems.

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Verlag
CRC Press
Erscheinungsdatum
2026
Sprache
Englisch
ISBN 10 
1032250178
ISBN 13 
9781032250175
Einband
Gebundene Ausgabe
Anzahl der Seiten
424
Kontakt zum Hersteller
preigu GmbH & Co. KG
mail@preigu.de

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