Intelligent Fault Detection and Diagnosis Techniques for Monitoring Wind and Solar Systems - Couverture souple

Mansouri

Couverture souple

ISBN 10 : 0443450161 ISBN 13 : 9780443450167

Editeur : Elsevier, 2025

Synopsis

Intelligent Fault Detection and Diagnosis Techniques for Monitoring Wind and Solar Energy Systems provides innovative solutions for fault detection and diagnosis in renewable energy systems. By leveraging advanced AI-based techniques such as deep learning, multiscale representation, and statistical analysis, this book aims to enhance system reliability, performance, and cost-efficiency. Readers will gain insights into the fundamentals of FDD processes tailored for photovoltaic and wind turbine operations. The book delves into data preprocessing techniques, feature extraction and selection methods, and optimization of deep learning models.

It also includes case studies and explores future directions for AI and machine learning in renewable energy, making it valuable for researchers, engineers, and policy makers.

A propos du livre

À propos des auteurs

Dr. Majdi Mansouri is an Associate Professor, at the Department of Electrical and Computer Engineering, Sultan Qaboos University, in the Sultanate of Oman. A Senior Member of the IEEE, he received this Ph.D. degree in electrical engineering from the University of Technology of Troyes (UTT), France, in 2011, and the H.D.R. degree (accreditation to supervise research) in electrical engineering from the University of Orleans, France, in 2019. From 2011 to 2024, he held different research positions at Texas A&M University at Qatar, in Doha. Since September 2024, he has been with Sultan Qaboos University as an Associate Professor. Dr. Mansouri has authored more than 250 publications, as well as the book 'Data-Driven and Model-Based Methods for Fault Detection and Diagnosis' (Elsevier, 2020). His research interests include the development of model-based, data-driven, and AI-based techniques for fault detection and diagnosis.is a member of IEEE.

Dr. Abdelmalek Kouadri is a Professor of Electrical Engineering at the Institute of Electrical and Electronics Engineering, University M'Hamed Bougara of Boumerdès, in Algeria. He has more than 15 years of combined academic and industrial experience. His research interests relate to systems engineering and control, with emphasis on process modelling, monitoring, and estimation. Prof. Kouadri has published more than 80 refereed journal and conference publications as well as book chapters. He has served as a technical committee member of several international journals and conferences.

Dr. Mansour Hajji is an Assistant Professor at the Higher Institute of Applied Science and Technology of Kasserine, Kairouan University, Tunisia, where he has been working since 2013. He received his Ph.D. degree in electrical engineering from the National Engineering School of Tunis (ENIT), Tunis, in 2013. Dr. Hajji is the author of several publications, and his current research interests include electrical machines, design and control, and machine learning techniques for fault detection and diagnosis.

Dr. Mohamed Faouzi Harkat is a Professor in the Department of Electronics, at Badji Mokhtar - Annaba University, Algeria, which he joined in 2004. He received his Ph.D. degree from the Institut National Polytechnique de Lorraine (INPL), France, in 2003. From 2002 to 2004, he was an Assistant Professor at the School of Engineering Sciences and Technologies of Nancy (ESSTIN), France. Prof. Harkat has over twenty years of research and practical experience in systems engineering and process monitoring. He is the author of more than 100 refereed journal and conference publications, as well as book chapters, and has served as an Associate Editor and in technical committees of several international journals and conferences.

Dr. Hazem N. Nounou is a Professor and Program Chair of the Electrical Engineering Program in the College of Science and Engineering at Hamad Bin Khalifa University (HBKU), in Qatar. Prior to joining HBKU, he was the Senior Associate Dean for Undergraduate Studies and Student Success and Professor of Electrical and Computer Engineering at Texas A&M University at Qatar. He received the B.S. degree (Magna Cum Laude) from Texas A&M University, College Station, in 1995, and the M.S. and Ph.D. degrees from Ohio State University, Columbus, in 1997 and 2000, respectively, all in electrical engineering. In 2001, he was a Development Engineer for PDF Solutions, a consulting firm for the semiconductor industry, in San Jose, CA. Then, in 2001, he joined the Department of Electrical Engineering at King Fahd University of Petroleum and Minerals in Dhahran, Saudi Arabia, as an Assistant Professor. In 2002, he moved to the Department of Electrical Engineering, United Arab Emirates University, Al-Ain, UAE. In 2007, he joined the Electrical and Computer Engineering Program at Texas A&M University at Qatar, Doha, Qatar. He was the holder of Itochu Professorship from 2015-2017. He published more than 200 refereed journal and conference papers and book chapters. He served as an Associate Editor and in technical committees of several international journals and conferences. His research interests include data-based control, intelligent and adaptive control, control of time-delay systems, and system monitoring, identification and estimation. Dr. Nounou is a senior member of IEEE.

Détails de l'édition

• Éditeur: Elsevier
• Date d'édition: 2025
• Langue: anglais
• ISBN 10: 0443450161
• ISBN 13: 9780443450167
• Reliure: Broché
• Nombre de pages: 190
• Coordonnées du fabricant: ELSEVIER; https://www.elsevier.com/es-es; ; Mooswaldallee 6; Freiburg; 79108; Allemagne