Fuzzy Set Theory and Fault Tree Analysis based Method Suitable for Fault Diagnosis of Power Transformer

Abstract

The fault detection and analysis for power transformer are the key measures to improve the security of power systems and the reliability of power supply. Due to the complicity of the power transformer structure and the variations in operating conditions, the occurrence of a fault inside power transformer is uncertain and random. Until now, the fault statistics of power transformer is very limited due to the low fault rate. A novel fault tree analysis method based on fuzzy set theory is proposed for power transformer. Using this method, the index of fault rate can be converted into fuzzy number of fault rate. The method of expert grading can be used to perform the probability of fault estimation without the requirement for corresponding statistics information. The details of fuzzy number design are described in the paper and an application example of the method is also provided. The results show that the proposed fuzzy fault tree analysis method is flexible and adaptive for fault diagnose of power transformer. Therefore, it is a useful engineering tool for the fault analysis and prevention of power transformer.