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Frequency Response Analysis (FRA) is an important tool used for diagnostic measurements of power transformers. Standard test configuration applied in the industry is the end-to-end open test setup; however, an interwinding capacitive configuration is also used. This paper presents a method-Cross Test Comparison (CTC)-for simultaneous analysis of results coming from both the mentioned test setups. Such an approach could offer a more sensitive tool for detecting some faults; moreover, it takes into consideration the influence of both voltage sides of a transformer in a one test result. The authors have used several indices to quantitatively assess the test results and proposed new approach to data interpretation. CTC method was tested using data from measurements performed in three cases: a unit tested in laboratory with introduced controlled deformations; transformers measured under industrial conditions; and a transformer with FRA changes resulting from tap-changer operations. The results showed that CTC method is more effective at detecting faults on the basis of FRA measurements.

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Frequency response analysis is a method used in transformer diagnostics for the detection of mechanical faults or short-circuits in windings. The interpretation of test results is often performed with the application of numerical indices. However, usually these indices are used for the whole frequency range of the recorded data, returning a single number. Such an approach is inaccurate and may lead to mistakes in the interpretation. An alternative quality assessment is based on the estimation of the local values of the quality index with the moving window method. In this paper, the authors analyse the influence of the width of the input data window for four numerical indices. The analysis is based on the data measured on the transformer with deformations introduced into the winding and also for a 10 MVA transformer measured under industrial conditions. For the first unit the analysis is performed for various window widths and for various extents of the deformation, while in the case of the second the real differences between the frequency response curves are being analysed. On the basis of the results it was found that the choice of the data window width significantly influences the quality of the analysis results and the rules for elements number selection differ for various numerical indices.