Substation transformer failure analysis through text mining

Nanthiine Nair Ravi, Sulfeeza Mohd Drus, Prajindra Sankar Krishnan, Nur Laila Abdul Ghani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Transformer failure could occur in terms of tripping that results in an unplanned or unseen outage. A good maintenance strategy is therefore an essential component in a power system to prevent unexpected failures. In this paper, the causes of transformer failure within the power transformer systems have been reviewed. Data is obtained from the transmission substation assets from the whole of Peninsular Malaysia for the past 5 years. However, the challenge is that the problem descriptions of the datasets are all in text formats. Thus, text mining approach is chosen for the data analysis using R. This paper covers the most common steps in R, from data preparation to analysis, and visualization through wordcloud generation. This study mainly focuses on bag-of-word text analysis approaches, which means that only word frequencies per text are used and word positions are ignored. Although this simplifies text content dramatically, research and many applications in the real world show that word frequencies alone contain adequate information for many types of analysis. As a result of analysis, keywords like "leak", "lightning", "animal", "cable" and "temperature" are identified as the main causes of transformer failures based on the number of word frequency in the tripping dataset. Further enhancement could be made in the future to predict the failure beforehand using predictive analytics approaches.

Original languageEnglish
Title of host publicationISCAIE 2019 - 2019 IEEE Symposium on Computer Applications and Industrial Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages293-298
Number of pages6
ISBN (Electronic)9781538685464
DOIs
Publication statusPublished - Apr 2019
Event9th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2019 - Kota Kinabalu, Malaysia
Duration: 27 Apr 201928 Apr 2019

Publication series

NameISCAIE 2019 - 2019 IEEE Symposium on Computer Applications and Industrial Electronics

Conference

Conference9th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2019
CountryMalaysia
CityKota Kinabalu
Period27/04/1928/04/19

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Computer Science Applications
  • Energy Engineering and Power Technology
  • Industrial and Manufacturing Engineering

Cite this

Ravi, N. N., Mohd Drus, S., Krishnan, P. S., & Laila Abdul Ghani, N. (2019). Substation transformer failure analysis through text mining. In ISCAIE 2019 - 2019 IEEE Symposium on Computer Applications and Industrial Electronics (pp. 293-298). [8743719] (ISCAIE 2019 - 2019 IEEE Symposium on Computer Applications and Industrial Electronics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAIE.2019.8743719