High performance electrical transformers are very costly and have a long (50+ years) running time. In general, they have few defects, but if they do, the impact on the electrical grid can be catastrophic.

The goal of this project is to better understand and predict the failure cases of those electrical transformers through a series of sensors. The goal is to predicts anomalies and schedule maintenance on the transformers more efficiently than the currently used fixed intervals.