Inversion Detection Method for Resistivity of Oil-Immersed Paper in Transformer

Oil-immersed paper is a weak link in internal insulation of oil immersed power transformer, whose aging state distributes inhomogeneously. However, most of the current assessment methods fail to consider the spatial distribution of aging areas inside transformer. Aiming at this problem, this paper proposes the inversion detection method to obtain the resistivity of oil-immersed paper in various regions nondestructively, and uses the resistivity of oil-immersed paper to assess directly the insulation state of oil immersed power transformers. Finite element method is applied to establish the mapping relationship between the resistivity of oil-immersed paper in different regions, and the dielectric loss factor obtained from the port of transformer. Back propagation neural network is used to learn inversely this mapping relationship so as to calculate the resistivity. Applying the proposed method on a 10-kV transformer, the calculated results are close to the measured values. The study shows that the inversion method can effectively calculate the oil-immersed resistivity in various regions, which represent the aging state in different regions of the transformer.