Transformer fault analysis based on rough sets and improved gravity algorithms

Abstract

Transformer is one of the most important equipment of power grid, in order to ensure the safe and reliable operation of power grid, the correct diagnosis of transformer fault is very important. Rough set theory is a new field of mathematical science, and it is applicable to many fields, including pattern recognition, machine learning, decision support, process control, and predictive models. Considering the incompleteness and complexity of transformer fault diagnosis data, a fault diagnosis method based on rough set theory and improved gravity algorithm is proposed in this paper.