Application of Logistic Regression Algorithm in the Interpretation of Dissolved Gas Analysis for Power Transformers

Dissolved gas analysis (DGA) is one of the regular routine tests accepted by worldwide utilities to detect power transformer incipient faults. While DGA measurement has fully matured since development offline and online sensors, interpretation results still calls for advanced approaches automate standardize process. Current industry practice relies on various techniques that are reported be inconsistent and, in some cases, unreliable. This paper presents a new application logistic regression algorithm improve reliability In this regard, regularized used accuracy Results reveal superior features proposed approach over conventional artificial intelligence presented literature.