The analysis of transformers condition based on Bayes-discriminant method with fault-tree fuzzy evaluation

China's electric power construction is renewing Increasingly, and the network is complex and changeable where the automation is getting higher. In this paper, Fuzzy evaluation system is established according to fault tree, and the estimation of transformer’s state is judged by analytic hierarchy process. Bayes-discriminant and discriminant formula are used to discriminate transformer’s attributes, which are based on historical data. The machine identification of transformer faults combines the fuzzy evaluation and Bayes-discriminant. It’s accuracy can be improved by correcting parameters. This method can effectively avoid subjective interference caused by artificial weights. The example shows that this method could be applied to judge health status of electric power equipment and this method can play an early-warning role in the operation of monitoring system.