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Digital Twin Technology in Condition Monitoring of Wind Turbines

by Nkosinathi Madushele , Obafemi O. Olatunji , Paul A. Adedeji
Save 35% Save 35%
Current price ₹14,527.00
Original price ₹22,348.00
Original price ₹22,348.00
Original price ₹22,348.00
(-35%)
₹14,527.00
Current price ₹14,527.00

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Book cover type: Hardcover
  • ISBN13: 9781032250175
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: CRC Press
  • Publisher Imprint: CRC Press
  • Publication Date:
  • Pages: 376
  • Original Price: GBP 175.0
  • Language: English
  • Edition: 1
  • Item Weight: 731 grams
  • BISAC Subject(s): Mechanical

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. Discussed the tools and enabling technologies for DT along with benefits and challenges.

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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