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

Author:

Araujo Mateus M.ORCID,Almeida Otacilio M.,Barbosa Fabio R.,Menezes Abraão G. C.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference18 articles.

1. Barbosa FR et al (2012) Application of an artificial neural network in the use of physicochemical properties as a low-cost proxy of power transformers DGA data. IEEE Trans Dielectr Electr Insul 19(1):239–246

2. Menezes AGC, Almeida OM, Barbosa FR (2018) Use of data mining algorithm to extract information contained in chromatographic data for the analysis of dissolved. IEEE CPE Power Eng

3. IEEE Guide for the Interpretation of Gases Generated in Mineral Oil-Immersed Transformers. IEEE Standard C57.104-2019

4. IEC (2015) Mineral oil-impregnated electrical equipment in service–guide to the interpretation of dissolved and free gases analysis. IEC 60599-2015

5. Halstead WD (1973) A thermodynamic assessment of the formation of gaseous hydrocarbons in faulty transformers. J Inst Petrol 59(9):239–241

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