Predictive Maintenance Of Railway Transformer Oil Based On Periodic Content Analysis

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

Text JT-27-71-101.PDF Download (1MB)

Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Commuter service, Dielectric, Oil analysis, Predictive maintenance, Transformer oil
Divisions:	Faculty of Mechanical Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	09 Jul 2021 17:55
Last Modified:	09 Jul 2021 17:55
URI:	http://eprints.utem.edu.my/id/eprint/25182
Statistic Details:	View Download Statistic

Actions (login required)

View Item