Probabilistic transformer fault tree analysis using Bayesian networks

This paper describes a novel application of probabilistic Bayesian networks for the identification of faulty conditions in power transformers, based on the well-known fault tree analysis procedure. The proposed technique emulates human judgment by the construction of a Bayesian net which closely resembles the structure of a typical expert-built power transformer fault tree. The proposed solution will be exemplified with test data from real cases.