Authors : Moma Munga Ferdinand; Lumanji Mbunga Luc; Mavungu Mayela Alain; Tshikudi Tshikudi Dennis; Minda Mwilambwe Georges

Volume/Issue : Volume 11 - 2026, Issue 10 - October

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Google Scholar : https://tinyurl.com/m62b3xrm

DOI : https://doi.org/10.38124/ijisrt/26Oct417

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : This article applies the concepts of a companion paper to the design of a monitoring and diagnosis system for the power transformers of a 120 kV substation supplying a copper–cobalt operation. Because continuous dissolved gas records were not available on site, the models were developed on a public simulated data set of 4,000 samples described by four gases (H₂, CO, C₂H₂, C₂H₄) and four states: normal, partial discharge, thermal fault and arc discharge.

Keywords : Dissolved Gas Analysis, Power Transformer, Random Forest, Stacking, Fault Diagnosis, Predictive Maintenance, Mining Substation.

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