A Novel Transformer Fault Diagnosis Model Based on Integration of Fault Tree and Fuzzy Set

This paper presents a new transformer fault diagnosis model based on the integration of fault tree analysis (FTA) and fuzzy set theory. In practical application, FTA is a frequently used technique in hazard identification. However, in conventional FTA, fuzzy information and uncertain logical relationship cannot be handled efficiently because of lack of fuzzy processing capability. Moreover, due to deficiency in data, the failure rates of the system components and the occurrence probability of undesired events cannot be obtained easily. In order to overcome these disadvantages, an integration of FTA and the fuzzy set theory is proposed to establish a fault diagnosis model, taking advantages of both methods. The analytic hierarchy process (AHP) is applied to determine the weights of tree node variables. The proposed model has been applied successfully and the result indicates the fuzzy fault tree analysis method (FFTA) has great potential in transformer fault diagnosis field.