Power Transformer Online Monitoring using Electromagnetic Waves explores how to use electromagnetic wave technology and remote monitoring systems to predict and localize costly mechanical defects and partial discharge challenges in high voltage transformer windings. This innovative approach brings several potential benefits compared with conventional techniques such as frequency response analysis, including impermeability to ambient noise, and online implementation capability. This book reviews both fundamental and state-of-the-art information about all key aspects of condition monitoring using electromagnetic waves. It addresses the simulation of power transformers in CST environment while also explaining the theoretical background of boundary conditions used. Chapters review how to achieve practical online implementation, reliable diagnosis, asset management and remnant life estimation. Partial discharge detection is also discussed.
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Gevork B. Gharehpetian received his PhD degree in electrical engineering from Tehran University, Tehran, Iran. As a PhD student, he received a scholarship from DAAD (German Academic Exchange Service) and he was with High Voltage Institute of RWTH Aachen, Aachen, Germany. He has been Assistant Professor then Full Professor at Amirkabir University of Technology (AUT) since 1997. He has been selected for numerous awards as a distinguished researcher from groups such as Ministry of Science Research and Technology (MSRT) and Iranian Association of Electrical and Electronics Engineers (IAEEE). Prof. Gharehpetian is a senior member and member of CIGRE, IEEE and IAEEE, respectively. He is Editor-in-Chief of the Journal of IAEEE, and has contributed to numerous works from international publishers of repute. His teaching and research interests include Smart Grid, Microgrids, Distributed Generation, FACTS and HVDC Systems, Monitoring of Power Transformers and its Transients.
Power Transformer Online Monitoring using Electromagnetic Waves explores how to use electromagnetic wave technology and remote monitoring systems to predict and localize costly mechanical defects and partial discharge challenges in high voltage transformer windings. This innovative approach brings several potential benefits compared with classic techniques such as frequency response analysis, including impermeability to ambient noise, and online implementation capability. The book reviews both fundamental and state-of-the-art information about all key aspects of condition monitoring using electromagnetic waves. It addresses the simulation of power transformers in CST while also explaining the theoretical background of boundary conditions used. Chapters review how to achieve practical online implementation, reliable diagnosis, asset management and remnant life estimation. Partial discharge detection is also discussed.
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Kartoniert / Broschiert. Condición: New. Discusses the advantages and disadvantages of the electromagnetic wave method in comparison with classical monitoring methods Explores how to design and implement power transformer monitoring systems using electromagnetic waves In. Nº de ref. del artículo: 571460402
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Taschenbuch. Condición: Neu. Neuware - Power Transformer Online Monitoring using Electromagnetic Waves explores how to use electromagnetic wave technology and remote monitoring systems to predict and localize costly mechanical defects and partial discharge challenges in high voltage transformer windings. This innovative approach brings several potential benefits compared with conventional techniques such as frequency response analysis, including impermeability to ambient noise, and online implementation capability. This book reviews both fundamental and state-of-the-art information about all key aspects of condition monitoring using electromagnetic waves. It addresses the simulation of power transformers in CST environment while also explaining the theoretical background of boundary conditions used. Chapters review how to achieve practical online implementation, reliable diagnosis, asset management and remnant life estimation. Partial discharge detection is also discussed. Nº de ref. del artículo: 9780128228012
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