Fault detection using FRA in order to improve the aging model of power transformer

Abstract

Power transformers are constantly exposed to mechanical, thermal and electrical stresses during operation. In this paper, the authors propose an improved aging model of power transformers by adding the impact of mechanical deteriorations. In the current practice, the mechanical deformation and dislocation of the windings and core are not sufficiently distinguished as components that influence the aging of the transformer. Hence, the current aging model was expanded with a functional block that contains several typical failures in order to emphasize their impact on the lifetime of transformers and their aging as well. The authors used the Frequency Response Analysis (FRA) method for the fault detection and location of the mechanical deformations of its active parts. The correlation function is used to determine the level of the detected failure. All presented test results are obtained in real exploitation conditions.