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Data mining techniques for transformer failure prediction model: A systematic literature review

Classification (of information); Forecasting; Industrial electronics; Outages; Power transformers; Preventive maintenance; Classification algorithm; Data mining algorithm; Maintenance strategies; Performance measurements; Prediction techniques; Predictive maintenance; Systematic literature review; T...

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Main Authors: Ravi N.N., Mohd Drus S., Krishnan P.S.
Other Authors: 57205240347
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-247062023-05-29T15:26:05Z Data mining techniques for transformer failure prediction model: A systematic literature review Ravi N.N. Mohd Drus S. Krishnan P.S. 57205240347 56330463900 36053261400 Classification (of information); Forecasting; Industrial electronics; Outages; Power transformers; Preventive maintenance; Classification algorithm; Data mining algorithm; Maintenance strategies; Performance measurements; Prediction techniques; Predictive maintenance; Systematic literature review; Transformer failure; Data mining Transformer failure may occur in terms of tripping, resulting in an unplanned or unseen failure. Therefore, a good maintenance strategy is an essential component of a power system to prevent unanticipated failures. Routine preventive maintenance programs have traditionally been used in combination with regular tests. However, in recent years, predictive maintenance has become prevalent due to the demanding industrial needs. Due to the increased requirement, utilities are persistently looking for ways to overcome the challenge of power transformer failures. One of the most popular ways for fault prediction is data mining. Data mining techniques can be applied in transformer failure prediction to provide the possibility of failure occurrence. Thus, this study aims to identify the common data mining techniques and algorithms that are implemented in studies related to various transformer failure types. The accuracy of each algorithm is also studied in this paper. A systematic literature review is carried out by identifying 160 articles from four main databases of which 6 articles are chosen in the end. This review found that the most common prediction technique used is classification. Among the classification algorithms, ANN is the prominent algorithm adopted by most of the researchers which has provided the highest accuracy compared to other algorithms. Further research can be done to investigate more on the transformer failures types and fair comparison between multiple algorithms in order to get more precise performance measurement. � 2019 IEEE. Final 2023-05-29T07:26:05Z 2023-05-29T07:26:05Z 2019 Conference Paper 10.1109/ISCAIE.2019.8743987 2-s2.0-85069153763 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069153763&doi=10.1109%2fISCAIE.2019.8743987&partnerID=40&md5=14e25b23e9cdf9b09d69b7e324ed4d3e https://irepository.uniten.edu.my/handle/123456789/24706 8743987 305 309 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Classification (of information); Forecasting; Industrial electronics; Outages; Power transformers; Preventive maintenance; Classification algorithm; Data mining algorithm; Maintenance strategies; Performance measurements; Prediction techniques; Predictive maintenance; Systematic literature review; Transformer failure; Data mining
author2 57205240347
author_facet 57205240347
Ravi N.N.
Mohd Drus S.
Krishnan P.S.
format Conference Paper
author Ravi N.N.
Mohd Drus S.
Krishnan P.S.
spellingShingle Ravi N.N.
Mohd Drus S.
Krishnan P.S.
Data mining techniques for transformer failure prediction model: A systematic literature review
author_sort Ravi N.N.
title Data mining techniques for transformer failure prediction model: A systematic literature review
title_short Data mining techniques for transformer failure prediction model: A systematic literature review
title_full Data mining techniques for transformer failure prediction model: A systematic literature review
title_fullStr Data mining techniques for transformer failure prediction model: A systematic literature review
title_full_unstemmed Data mining techniques for transformer failure prediction model: A systematic literature review
title_sort data mining techniques for transformer failure prediction model: a systematic literature review
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806426396382199808
score 13.214268

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