Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/483928
Title: Detection and classification of internal faults in power transformer with effective diagnosing techniques
Researcher: Umasankar L
Guide(s): Kalaiarasi N
Keywords: Engineering and Technology
Engineering
Engineering Electrical and Electronic
power transformer
engineering technology
diagnosis of transformers
University: Anna University
Completed Date: 2021
Abstract: targets the demand for optimized tools and techniques to estimate the newlineperformance of modern transformers has increased. The renewed thrust in newlinesmart power system networks along with the development of advanced newlinemethods in the monitoring and diagnostics has resulted in major impetus to newlineresearch in the associated domain. newlineAs an integrated part of a power system, the Power Transformers have newlinean issue. Any fault in the transformer can induce a severe outage, which newlinetherefore requirements continuous monitoring and diagnostics of its newlineoperation. newlineThe different fault diagnosis strategies are assumed to distinguish the newlinefaults in the power transformer and have to extinguish the effects of the faults newlineat the initial stage and to avoid the interruption of power supply. Fault newlinediagnosis of transformers plays an active role in power system monitoring and newlinecontrol that ensures a stable and continuous electrical power supply to newlineconsumers. newline
Pagination: xxiv, 249p
URI: http://hdl.handle.net/10603/483928
Appears in Departments:Faculty of Electrical Engineering

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01_title.pdfAttached File60.95 kBAdobe PDFView/Open
02_prelim.pdf1.67 MBAdobe PDFView/Open
03_content.pdf15.03 kBAdobe PDFView/Open
04_abstract.pdf11.54 kBAdobe PDFView/Open
05_chapter 1.pdf108.51 kBAdobe PDFView/Open
06_chapter 2.pdf165.63 kBAdobe PDFView/Open
07_chapter 3.pdf516.84 kBAdobe PDFView/Open
08_chapter 4.pdf874.21 kBAdobe PDFView/Open
09_chapter 5.pdf175.85 kBAdobe PDFView/Open
10_annexures.pdf116.44 kBAdobe PDFView/Open
80_recommendation.pdf72.85 kBAdobe PDFView/Open
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