C. Chan

Transformer Fault Classification Based on Dissolved Gas Compositions Using Microsoft Azure Machine Learning

This study presents a novel diagnostic methodology for oil-filled transformers, leveraging dissolved gas analysis (DGA) and a no-code machine learning framework. Conventional diagnostic methods such as Duval Triangle and gas ratio techniques are constrained by limited adaptability to modern transformer designs, suscept...