eprintid: 20479
rev_number: 3
eprint_status: archive
userid: 1
dir: disk0/00/02/04/79
datestamp: 2026-01-29 06:29:14
lastmod: 2026-01-29 06:29:14
status_changed: 2026-01-29 06:29:14
type: article
metadata_visibility: show
creators_name: Bakar, Norazhar Abu
creators_name: Chairul, Imran Sutan
creators_name: Ghani, Sharin Ab
creators_name: Khiar, Mohd Shahril Ahmad
creators_name: Wanik, Mohd Zamri Che
title: Improvement of transformer dissolved gas analysis interpretation using J48 decision tree model
ispublished: pub
note: Cited by: 6; All Open Access, Gold Open Access
abstract: Dissolved gas analysis (DGA) is widely accepted as an effective method to detect incipient faults within power transformers. Gases such as hydrogen, methane, acetylene, ethylene and ethane are normally utilized to identify the transformer fault conditions. Several techniques have been developed to interpret DGA results such as the key gas method, Doernenburg, Rogers, International Electro Technical Commission (IEC) ratio-based methods, Duval triangles, and the latest Duval pentagon methods. However, each of these approaches depends on the experts' shared knowledge and experience rather than quantitative scientific methods, therefore different diagnoses may be reported for the same oil sample. To overcome these shortcomings, this paper proposed the use of decision tree method to interpret the transformer health condition based on DGA results. The proposed decision tree model employed three main fault gases; methane, acetylene, ethylene as inputs, and classified the transformer into eight fault conditions. The J48 algorithm is used to train and developed the decision tree model. The performance of the proposed model is validated with the pre-known condition of transformers and compared with the Duval triangle method (DTM). Results show that the proposed model delivers better precision and accuracy in predicting transformer fault conditions compared to DTM with 81 and 69 respectively. © 2023, Institute of Advanced Engineering and Science. All rights reserved.
date: 2023
publisher: Institute of Advanced Engineering and Science
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140775349&doi=10.11591%2fijai.v12.i1.pp48-56&partnerID=40&md5=10f4874ba8112efa722f6085c65351aa
id_number: 10.11591/ijai.v12.i1.pp48-56
full_text_status: none
publication: IAES International Journal of Artificial Intelligence
volume: 12
number: 1
pagerange: 48 – 56
refereed: TRUE
issn: 20894872
citation:   Bakar, Norazhar Abu and Chairul, Imran Sutan and Ghani, Sharin Ab and Khiar, Mohd Shahril Ahmad and Wanik, Mohd Zamri Che  (2023) Improvement of transformer dissolved gas analysis interpretation using J48 decision tree model.  IAES International Journal of Artificial Intelligence, 12 (1).  48 – 56.  ISSN 20894872