Detection of mechanical deformation in old aged power transformer using cross correlation co-efficient analysis method

Abstract

Detection of minor faults in power transformer active part is essential because minor faults may develop and lead to major faults and finally irretrievable damages occur. Sweep Frequency Response Analysis (SFRA) is an effective low-voltage, off-line diagnostic tool used for finding out any possible winding displacement or mechanical deterioration inside the transformer which happens due to large electromechanical forces occurring from the fault currents or due to transformer transportation and relocation. 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 which has occurred in the active part of transformer. But in old aged transformers, the primary reference response is unavailable. So, Cross Correlation Co-Efficient (CCF) measurement technique can be a new approach for fault detection in these transformers. In this thesis, mathematical analysis of transfer function for SFRA technique has been elaborated, mathematical model for calculating CCF between SFRA curves has been programmed and through several case studies, the developed model has been applied on some faulty transformer. It has been found that theoretically predicted results using CCF matches with practical results which indicate the effectiveness of the newly proposed method. The case studies are based on several 132 kV & 230 kV healthy and faulty power transformers manufactured by Bangladesh, China, India and England.