A Synthetic Condition Assessment Model for Power Transformers Using the Fuzzy Evidence Fusion Method

Condition-based maintenance decision-making of transformers is essential to electric enterprises for avoiding financial losses. However, precise transformer condition assessment was tough to accomplish because of the negligence of the influence of bushing and accessories, the difficulty of fuzzy grade division, and the lack of reasonable fuzzy evidence fusion method. To solve these problems, a transformer assessing model was proposed in the paper. At first, an index assessing system, considering the main body, the bushing and the accessories components, was established on the basis of components division of transformers. Then, a Cauchy membership function was employed for fuzzy grades division. Finally, a fuzzy evidence fusion method was represented to handle the fuzzy evidences fusion processes. Case studies and the comparison analysis with other methods were performed to prove the effectiveness of this model. The research results confirm that the proposed model could be recommendation for condition based maintenance of power transformers for electric enterprises.