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Enhancing gas formation theory assessment in power transformers by using decision tree transparency and new guess into decomposition temperatures of insulating mineral oil

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Abstract

The analysis of gases dissolved in oil is the main technique used to predict possible failures in power transformers. Currently, there are some assessment algorithms for the predictive analysis, but all of them have in common the fact that they are based on the classical gas formation theory. This work aims to analyze the use of decision trees (DTs) for the analysis of gases dissolved in mineral oil, also establishing a relationship associated with decision making during the formation of trees and the formation of gases. In this way, some important aspects involving the insulating mineral oil can be better understood and quantified. For this purpose, one dataset containing 201 samples is used in the study. The results provided by the tree are arranged in a Cartesian plane, and the gases are analyzed based on the ratios used by Doernenburg. DT is discussed in detail to validate the algorithm performance based on the classical gas formation theory.

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Data availability

The power transformer failures dataset used in this paper is available at https://dx.doi.org/10.21227/h8g0-8z59.

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Acknowledgements

The authors would like to thank Foundation to Support Research in State of Piaui/Coordination of Improvement of Higher Education Personnel (FAPEPI/CAPES) for the support, as well Postgraduate Program in Electrical Engineering-Federal University of Piaui (PPGEE-UFPI) and Equatorial Electricity Utility Company for educational and technical support, respectively.

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Authors and Affiliations

  1. Department of Technical and Commercial Services, Equatorial Electricity Utility Company, Teresina, Brazil

    Mateus M. Araujo

  2. Department of Electrical Engineering, Federal University of Piaui, Teresina, Brazil

    Otacilio M. Almeida & Fabio R. Barbosa

  3. Department of Operational Studies, Equatorial Electricity Utility Company, Teresina, Brazil

    Abraão G. C. Menezes

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  1. Mateus M. Araujo
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  2. Otacilio M. Almeida
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  3. Fabio R. Barbosa
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  4. Abraão G. C. Menezes
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Correspondence to Mateus M. Araujo.

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Araujo, M.M., Almeida, O.M., Barbosa, F.R. et al. Enhancing gas formation theory assessment in power transformers by using decision tree transparency and new guess into decomposition temperatures of insulating mineral oil. Neural Comput & Applic 36, 3259–3266 (2024). https://doi.org/10.1007/s00521-023-09216-2

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