Implementation of normalization covariance factor calculation technique to detect mechanical deformation in power transformer

摘要

Sweep Frequency Response Analysis (SFRA) is an effective low-voltage, off-line diagnostic tool used to find out any possible winding displacement or mechanical deterioration inside the Transformer, due to large electromechanical forces occurring from the fault currents or due to Transformer transportation and relocation. SFRA curves are considered as finger prints of a transformer. In this method, the frequency response of a transformer is taken both at manufacturing industry and concern site. Then both the response is compared to predict the fault taken place in active part. Cross Correlation Co-efficient is the most popular parameter for this comparison. But Normalization Covariance Factor can also be an effective indicator to interpret SFRA curves. In this paper, with a small discussion on SFRA technique and Normalization Covariance Factor, the effectiveness of Normalization Covariance Factor for fault detection has been represented through several case studies.