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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 FRA technique through incorporating the magnitude and phase angle plots that can be measured using any commercial frequency response analyzer into one polar plot. In contrary with 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, 3D models for two 3-phase power transformers of different ratings, sizes and windings structures are modelled using finite element analysis (FEA) 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 DIP technique is able to detect minor fault levels of AD and DSV with high accuracy.

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One of the main drawbacks of the frequency response analysis (FRA) technique that is widely accepted as the most reliable tool to detect transformer internal mechanical deformations is the inconsistent interpretation of the measured signature because of its reliance on personal expertise more than standard codes. Moreover, conventional FRA signature has a very low accuracy in detecting incipient and low mechanical fault levels. In order to avoid inconsistent interpretation for the transformer FRA signatures and improve its accuracy to detect minor fault levels, a reliable automated technique has become essential. This paper investigates the feasibility of utilizing FRA polar plot to detect minor radial deformation levels within two, 3-phase power transformers of different ratings and winding configurations simulated using three-dimensional finite element analysis software. Simulation results are validated through experimental measurements. Results of this paper are also compared with the results obtained for other types of transformer winding deformations that are published in the literature in order to identify unique impact for each fault type on the proposed method. Findings reveal the superiority of the proposed approach over existing conventional technique in terms of accurate identification and quantification for minor transformer winding deformations.

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