Structural Control and Fault Detection of Wind Turbine Systems

Inbunden, Engelska, 2025

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With the rapid growth of wind energy worldwide, and the increasing size of wind turbine systems, addressing challenges in their operation and control is becoming increasingly important. These challenges affect all components of wind turbine systems, and require an integrated approach to optimize safety, cost, structural integrity and system survivability, while maintaining the desired performance quality.This book has established itself as a reliable reference for researchers and engineers in mechatronics and control, specifically for wind power, as well as for manufacturers of wind farm equipment and turbine systems. It conveys theoretical and practical techniques that are instrumental for the control of wind turbine systems, such as load analysis, control concepts, health diagnosis and monitoring, and fuzzy fault tolerant control.The new edition features revised as well as all-new chapters covering recent advances in the field, on both small turbines and large systems. Topics include numerical and experimental tools for turbine load analysis, health monitoring, control, transformer models, power prediction, robust fuzzy fault tolerant control, and use of digital twins.

Produktinformation

Utgivningsdatum2025-09-09
Mått156 x 234 x 22 mm
Vikt703 g
FormatInbunden
SpråkEngelska
SerieEnergy Engineering
Antal sidor372
Upplaga2
FörlagInstitution of Engineering and Technology
ISBN9781837241446

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Energiteknik inom Naturvetenskap och teknik

Hamid Reza Karimi is a professor in the Department of Mechanical Engineering of the Politecnico di Milano, Italy. His research interests include control systems and mechatronics. He serves as an ordinary member of Academia Europaea, a member of The European Academy of Science, a member of Agder Academy of Sciences and Letters in Norway, member of National Academy of Artificial Intelligence (NAAI), distinguished fellow of the International Institute of Acoustics and Vibration (IIAV), fellow of The International Society for Condition Monitoring (ISCM), fellow of the Asia-Pacific Artificial Intelligence Association, member of IFAC Technical Committees, member of the board of directors of the IIAV and member of Management Committee of the ISCM, and on key journal boards. A Web of Science highly cited researcher, his awards include the NAAI Distinguished Artificial Intelligence Scholar Award, a Japan Society for the Promotion of Science Award, an Alexander-von-Humboldt-Stiftung Fellowship Award, and the August-Wilhelm Scheer Visiting Professorship Award.

Chapter 1: Introduction to structural control and fault detection of wind turbine systemsChapter 2: Numerical and experimental tools for small wind turbine load analysisChapter 3: Structural control concept for load reduction of offshore wind turbinesChapter 4: Health monitoring of wind turbine: data-based approachesChapter 5: Health monitoring for wind turbine blades based on backpropagation neural network and acoustical featuresChapter 6: Health diagnosis and monitoring of wind turbines: deep learning-based methodsChapter 7: Damage detection and localization at the jacket support of an offshore wind turbine using transformer modelsChapter 8: Power prediction of offshore wind turbines based on advanced machine learning methodsChapter 9: Robust fuzzy fault tolerant control applied to wind energy systems subject to sensor faultsChapter 10: Digital twin-driven wind turbine bearing transmission system health managementChapter 11: Toward farm-level health management of wind turbine systems: status and scope for improvements