Knowledge discovery in neural networks with application to transformer failure diagnosis

The paper describes a new methodology for mapping a neural network into a rule-based fuzzy inference system. This mapping makes explicit the knowledge implicitly captured by the neural network during the learning stage, by transforming it into a set of rules. The method is applied in transformer fault diagnosis using dissolved gas-in-oil analysis. Studies on transformer failure diagnosis are reported, illustrating the good results obtained and the knowledge discovery made possible.