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Evaluation model of transformer state based on improved fuzzy comprehensive diagnosis theory

The state evaluation of transformer includes analysing many kinds of operating signals, but the relationship between those signals and transformer states is fuzzy. To clearly describe the relationship, a multi-level comprehensive fuzzy mathematics algorithm is used. The algorithm is based on the intelligent fuzzy diagnosis theory. Taking the power transformer as the research object, the factor set and comment set are selected through appropriate methods, and the membership function relationship between them is established. The selected factors come from the electrical test, the amount of gas in the oil, and the insulating oil. And the comment set is the division of the transformer status, which is uniformly divided into four evaluations. Considering the multi-level nature of factors, fuzzy inferences are carried out to determinate the membership function, and a weight set of the factor set is established through an improved analytic hierarchy process (IAHP). In addition, a two-level fuzzy evaluation example for evaluating the state of a transformer in operation is given, which verifies the effectiveness and feasibility of the evaluation model.