Application of DIP to Detect Power Transformers Axial Displacement and Disk Space Variation Using FRA Polar Plot Signature

Abstract

While frequency response analysis (FRA) technique has been successfully used to assess the mechanical integrity of active parts within power transformers, it still exhibits some drawbacks including its inability to detect incipient and minor winding deformations and the requirement for an expert to analyze the results. Although several papers have investigated the impact of various faults on the transformer FRA signature, no attempt was made to automate and improve the fault detection accuracy of the current technique. The main contribution of this paper is the presentation of a new approach for the FRA technique through incorporating the magnitude and phase angle plots that can be measured using any commercial frequency response analyzer into one polar plot. Contrary to the current industry practice that only relies on the magnitude of the measured FRA signature for fault identification and quantification, the proposed polar plot that comprises more features than the magnitude plot will facilitate the use of digital image processing (DIP) techniques to improve the detection accuracy, standardize, and automate the FRA interpretation process. In this regard, three-dimensional models for two three-phase power transformers of different ratings, sizes, and windings structures are modeled using a finite element analysis technique to simulate various levels of axial displacement (AD) and disk space variation (DSV) at different locations of the transformer windings. Impact of minor fault levels on the proposed polar plot signature is investigated through the application of various DIP techniques. Simulation results are validated through practical measurements on a scaled-down transformer. Results show that the proposed polar plot along with the DIP technique is able to detect minor fault levels of AD and DSV with high accuracy.