Performance Optimization of Fault Diagnosis Methods for Power Systems (Engineering Applications of Computational Methods, 9, Band 9) - Hardcover

Wu, Dinghui; Zhang, Juan; Fan, Junyan; Tang, Dandan

Hardcover

ISBN 10: 9811945772 ISBN 13: 9789811945779

Verlag: Springer, 2022

Inhaltsangabe

This book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear parameter varying algorithm, and data-driven ones, such as random matrix theory. Studies on fault diagnosis of power systems have long been the focus of electrical engineers and scientists. Pursuing a holistic approach to improve the accuracy and efficiency of existing methods, the underlying concepts toward several algorithms are introduced and then further applied in various situations for fault diagnosis of power systems in this book. The primary audience for the book would be the scholars and graduate students whose research topics including the control theory, applied mathematics, fault detection, and so on.

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Über die Autorin bzw. den Autor

Dr. Dinghui Wu received the Ph.D. degree in Control Science and Engineering with Jiangnan University and now is a Visiting Fellow with the School of Computer and electronic engineering, University of Denver, the US. His current research interests include energy optimization control technology, fault diagnosis of power systems, and edge calculation. Since Nov. 2019, Dr. Wu has been in School of Internet of Things Engineering, Jiangnan University, Wuxi, China, as a Professor. 

 

Ms. Juan Zhang received the master's degree in Electrical Engineering with Jiangnan University, China, in 2021. She began her doctoral program with Jiangnan University, China, in 2021. Her current research interests include fault diagnosis of power systems and random matrix theory.

 

Mr. Junyan Fan received master's degree in mechatronics engineering with Jiangsu Ocean University, China, in 2021. He began his doctoral program with Jiangnan University, China,in 2021. His current research interests include energy prediction and energy optimization.

 

Ms. Dandan Tang received the bachelor's degree in Electrical Engineering with Jiangnan University, China,in 2020. She began her master’s program with Jiangnan University, China, in 2020. Her current research interests include distributed fault diagnosis of deep learning and federated learning.

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This book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear parameter varying algorithm, and data-driven ones, such as random matrix theory. Studies on fault diagnosis of power systems have long been the focus of electrical engineers and scientists. Pursuing a holistic approach to improve the accuracy and efficiency of existing methods, the underlying concepts toward several algorithms are introduced and then further applied in various situations for fault diagnosis of power systems in this book. The primary audience for the book would be the scholars and graduate students whose research topics including the control theory, applied mathematics, fault detection, and so on.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2022
• Sprache: Englisch
• ISBN 10: 9811945772
• ISBN 13: 9789811945779
• Einband: Gebundene Ausgabe
• Auflage: 1
• Anzahl der Seiten: 140
• Kontakt zum Hersteller: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Deutschland