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Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis

The high frequency of operation of commuter trains, due to passenger demand as well as the selection of railway as the mode of daily transportation for commuting on weekdays, increases the usage of on-board power, especially for a train’s traction system. As maintenance is rarely performed on transf...

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Main Authors: Abdullah, Mohd Azman, Harun, Mohd Hanif, Mat Dan, Reduan, Habeeb, Hiyam Adil, Mohan, Ahmed Esmael, Othman, Megat Muhammad Haziq
Format: Article
Language:English
Published: Malaysian Tribology Society (Mytribos) 2020
Online Access:http://eprints.utem.edu.my/id/eprint/25182/2/JT-27-71-101.PDF
http://eprints.utem.edu.my/id/eprint/25182/
https://jurnaltribologi.mytribos.org/v27/JT-27-71-101.pdf
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spelling my.utem.eprints.251822021-07-09T17:55:41Z http://eprints.utem.edu.my/id/eprint/25182/ Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis Abdullah, Mohd Azman Harun, Mohd Hanif Mat Dan, Reduan Habeeb, Hiyam Adil Mohan, Ahmed Esmael Othman, Megat Muhammad Haziq The high frequency of operation of commuter trains, due to passenger demand as well as the selection of railway as the mode of daily transportation for commuting on weekdays, increases the usage of on-board power, especially for a train’s traction system. As maintenance is rarely performed on transformer oil, it deteriorates and negatively affects transformer performance, increases heat, and may damage the transformer as well. This will result in significantly costly maintenance expenses for train operators. Therefore, this paper proposes a predictive maintenance schedule for transformer oil. The recommendations are based upon an analysis of transformer oil contents and its properties over a 90-month period of operation. A linear correlation between the properties of the oil and the train’s period of operation yielded a predictive maintenance schedule, primarily reclamation and filtration, for the oil at the threshold of each property. Major oil changes are to be considered when all properties are approaching their thresholds. As oil deterioration increases over time, a specific maintenance schedule was suggested. This was tested and observed on several transformer units. The content analysis of each oil is also discussed. Based on the results, this predictive maintenance schedule can be used on other trains with the same transformer model or other trains using the same type of insulating oil. Malaysian Tribology Society (Mytribos) 2020-11 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25182/2/JT-27-71-101.PDF Abdullah, Mohd Azman and Harun, Mohd Hanif and Mat Dan, Reduan and Habeeb, Hiyam Adil and Mohan, Ahmed Esmael and Othman, Megat Muhammad Haziq (2020) Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis. Jurnal Tribologi, 27. pp. 71-101. ISSN 2289-7232 https://jurnaltribologi.mytribos.org/v27/JT-27-71-101.pdf
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description The high frequency of operation of commuter trains, due to passenger demand as well as the selection of railway as the mode of daily transportation for commuting on weekdays, increases the usage of on-board power, especially for a train’s traction system. As maintenance is rarely performed on transformer oil, it deteriorates and negatively affects transformer performance, increases heat, and may damage the transformer as well. This will result in significantly costly maintenance expenses for train operators. Therefore, this paper proposes a predictive maintenance schedule for transformer oil. The recommendations are based upon an analysis of transformer oil contents and its properties over a 90-month period of operation. A linear correlation between the properties of the oil and the train’s period of operation yielded a predictive maintenance schedule, primarily reclamation and filtration, for the oil at the threshold of each property. Major oil changes are to be considered when all properties are approaching their thresholds. As oil deterioration increases over time, a specific maintenance schedule was suggested. This was tested and observed on several transformer units. The content analysis of each oil is also discussed. Based on the results, this predictive maintenance schedule can be used on other trains with the same transformer model or other trains using the same type of insulating oil.
format Article
author Abdullah, Mohd Azman
Harun, Mohd Hanif
Mat Dan, Reduan
Habeeb, Hiyam Adil
Mohan, Ahmed Esmael
Othman, Megat Muhammad Haziq
spellingShingle Abdullah, Mohd Azman
Harun, Mohd Hanif
Mat Dan, Reduan
Habeeb, Hiyam Adil
Mohan, Ahmed Esmael
Othman, Megat Muhammad Haziq
Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis
author_facet Abdullah, Mohd Azman
Harun, Mohd Hanif
Mat Dan, Reduan
Habeeb, Hiyam Adil
Mohan, Ahmed Esmael
Othman, Megat Muhammad Haziq
author_sort Abdullah, Mohd Azman
title Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis
title_short Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis
title_full Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis
title_fullStr Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis
title_full_unstemmed Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis
title_sort predictive maintenance of railway transformer oil based on periodic content analysis
publisher Malaysian Tribology Society (Mytribos)
publishDate 2020
url http://eprints.utem.edu.my/id/eprint/25182/2/JT-27-71-101.PDF
http://eprints.utem.edu.my/id/eprint/25182/
https://jurnaltribologi.mytribos.org/v27/JT-27-71-101.pdf
_version_ 1706960989223649280
score 13.211869

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