Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan

This project describes the condition monitoring of oil-filled transformer utilizing Dissolved Gas Analysis. The main objective is to study and detect any defect in oil-filled transformer by using Dissolved Gas Analysis. Dissolved Gas Analysis is probably the most widely used condition monitoring tec...

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Main Author: Sainan, Syahrulazam
Format: Thesis
Language:English
Published: 2000
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/77958/1/77958.pdf
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spelling my-uitm-ir.779582023-07-26T00:34:03Z Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan 2000 Sainan, Syahrulazam TJ Mechanical engineering and machinery This project describes the condition monitoring of oil-filled transformer utilizing Dissolved Gas Analysis. The main objective is to study and detect any defect in oil-filled transformer by using Dissolved Gas Analysis. Dissolved Gas Analysis is probably the most widely used condition monitoring technique to monitor the operation of oil-filled transformers [1]. In order to use Dissolved Gas Analysis, the gas samples in those transformers have to be taken using accurate sampling technique. All the gas samples have to be analyzed to extract the gases and get the data for fault gases. Using this analysis, defect from fault gases in the transformer can be detected. A recommendation can be made so that proper action can be taken before the unit suffers additional damage. The scope of analysis covers only on the fault gases of oil-filled transformers. 2000 Thesis https://ir.uitm.edu.my/id/eprint/77958/ https://ir.uitm.edu.my/id/eprint/77958/1/77958.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Sheikh Rahimullah, Bibi Norasiqin
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Sheikh Rahimullah, Bibi Norasiqin
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Sainan, Syahrulazam
Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan
description This project describes the condition monitoring of oil-filled transformer utilizing Dissolved Gas Analysis. The main objective is to study and detect any defect in oil-filled transformer by using Dissolved Gas Analysis. Dissolved Gas Analysis is probably the most widely used condition monitoring technique to monitor the operation of oil-filled transformers [1]. In order to use Dissolved Gas Analysis, the gas samples in those transformers have to be taken using accurate sampling technique. All the gas samples have to be analyzed to extract the gases and get the data for fault gases. Using this analysis, defect from fault gases in the transformer can be detected. A recommendation can be made so that proper action can be taken before the unit suffers additional damage. The scope of analysis covers only on the fault gases of oil-filled transformers.
format Thesis
qualification_level Bachelor degree
author Sainan, Syahrulazam
author_facet Sainan, Syahrulazam
author_sort Sainan, Syahrulazam
title Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan
title_short Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan
title_full Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan
title_fullStr Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan
title_full_unstemmed Condition monitoring of oil filled transformer utilizing dissolved gas analysis / Syahrulazam Sainan
title_sort condition monitoring of oil filled transformer utilizing dissolved gas analysis / syahrulazam sainan
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2000
url https://ir.uitm.edu.my/id/eprint/77958/1/77958.pdf
_version_ 1783736187579531264