Abstract
Frequency Response Analysis (FRA) technique is commonly used to assess the mechanical integrity of power transformer core and windings. A few papers investigating the ability of FRA technique to detect bushing faults and transformer oil degradation can be found in the literatures. However, in all of these papers, only magnitude of the FRA signature along with visual analysis was used for fault identification and quantification which may lead to inconsistent conclusions for the same FRA signature when interpreted by various personnel. As such, there is an essential need to standardize and automate the FRA interpretation process to improve its reliability and accuracy. This paper is taking a step forward toward this goal through presenting a new FRA interpretation approach by incorporating the magnitude and phase angle plots of the measured FRA signature into one polar plot that comprises more features than the conventional magnitude plot currently used for fault diagnosis. Moreover, the proposed polar plot facilitates the application of digital image processing techniques (DIP) to automate and standardize the whole process. The new proposed technique is assessed through its application to detect minor transformer bushing faults and insulating oil degradations. In this regard, two transformers of different ratings, winding structure and physical dimensions are simulated using 3D finite element analysis to implement various levels of transformer bushing faults and oil degradation. The obtained FRA polar plots of the two investigated transformers under various bushings and oil health conditions are manipulated using the developed DIP codes to investigate the impact of each fault type / level on the proposed polar plot signature. Also, Practical measurements are performed to validate simulation results and evaluate the feasibility of the proposed technique. Results show the ability of the proposed technique to automate the detection of minor levels of bushing faults and insulating oil degradation with a high degree of accuracy.