Owa Operator-based Fuzzy Comprehensive Assessment of Transformer Condition

Abstract

The indicators system and indicators normalization method for the condition assessment of Transformer is developed and membership function of the indicators is established. The establishment of Expert Weight is decided jointly by subjective weight and objective weight which is based on entropy weight thoughts, while the indicators weight is gained by the weight which is derived from the standard Analytic Hierarchy Process and the expert weight. A comprehensive condition assessment model of transformer based on OWA(Ordered Weighted Averaging) operator and fuzzy assessment is proposed and divided into two layers, fuzzy polymerization is adopted for the second layer sub-indicators to get the fuzzy membership of the first layer main indicators, while OWA operator polymerized with the final comprehensive condition assessment of the transformer is adopted for the main indicators of the first layer. In order to fully consider the impact of indicators weight and membership on the condition assessment result, a fuzzy polymerization conversion function based on OWA operator is introduced in the model, so as to integrate the attribute information from various important information sources. Case analysis indicates that the condition assessment of transformer can be carried out by this method; the reasonable and objective conclusion is close to the true condition of transformer.