Non-Destructive Testing and Condition Monitoring Techniques in Wind Energy

Fausto Pedro Garcia Marquez, Mayorkinos Papaelias, Valter Luiz Jantara Junior

• Publisher: Academic Press
• Year: 2023
• Print ISBN:
  9780323996662
• eBook ISBN:
  9780323951005
• Topic: Technology & Engineering
• Subtopic: Economic Theory
• Index: Technology & Engineering

Non-Destructive Testing and Condition Monitoring Techniques in Wind Energy looks at the complex and critical components of energy assets and the importance of inspection and maintenance to ensure their high availability and uninterrupted operation. Presenting the main concepts, state-of-the-art advances and case studies, this book approaches the topic by considering it as an integral part of the overall operation of any wind energy project. Linking the essential NDT subject with its sub disciplines, the book uses computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques to support analysis of prognostic problems with defined constraints and requirements. This book is the first of its kind and will provide useful insights to industrial engineers and scientists, academics and students in the possibilities that NDT and condition monitoring technologies can offer. - Presents advances in Non-Destructive Techniques and Condition Monitoring Systems applied in the energy industry - Provides case studies in Fault Detection and Diagnosis and Prognosis for critical variability - Offers technical maintenance actions for the observation and analyses of inspection, monitoring, testing, diagnosis, prognosis and active maintenance actions in wind

Table of contents

• Cover
• Front Matter
• Table of Contents
• Copyright
• List of contributors
• Biographies
• Foreword
• Preface
• Introduction to non-destructive testing and condition monitoring techniques in wind energy
• List of Illustrations
• List of Tables
• 1 : SCADA-based fault detection in wind turbines: data-driven techniques and applications
• 2 : Fault detection in small wind turbines using condition monitoring techniques and machine learning algorithms (a predictive approach)
• 3 : Prediction and classification of different wind turbine alarms using K-nearest neighbors
• 4 : Artificial neural networks applied for wind turbines maintenance management in unmanned aerial vehicle acoustic inspection case
• 5 : Quantitative interlink wear estimation method for the mooring chain
• 6 : Enhanced sparse representation-based intelligent recognition framework for fault diagnosis of wind turbine drive trains
• 7 : An optimal combined production and maintenance policies for a wind farm with environmental and operational considerations
• 8 : The valuation of geothermal power projects in Indonesia using real options valuation
• 9 : A robust multiple open-switch fault diagnosis approach for converter in wind energy system
• 10 : Condition monitoring in wind turbines: a review
• 11 : Artificial intelligence techniques and cloud computing for wind turbine pitch bearing fault detection∗
• 12 : Alarms and false-alarm analysis by support vector machine in wind turbines
• 13 : Background, advancement, and applications of in situ structural health monitoring based on different modes of failure detection in composites: a review
• 14 : Numerical simulations of offshore wind farms considering accidental scenarios
• 15 : Multibody dynamic analysis of onshore horizontal-axis wind turbine
• 16 : Foundation monitoring system of offshore wind turbines
• Index
• A