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Abstract
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Abstract: The frequency response analysis (FRA) test has been recognised as one of the sensitive tools for detecting
electrical and mechanical faults inside power transformers. However, there is still no universally systematic
interpretation technique for these tests. Many research efforts have employed different statistical criteria in order to aid
the interpretative capability of the FRA, but it is shown that the methods used so far are based on parametric statistics,
which need a set of assumptions about the normality, randomness and statistical independence of FRA data.
Therefore, this study aims to propose some non-parametric statistical methods which are based on explicitly weaker
assumptions than such classical parametric methods. The proposed statistical methods are applied to the experimental
FRA measurements obtained from two test objects: a three phase distribution transformer (35/0.4 kV, 100 kVA) to study
the winding interturn fault and a two winding transformer (1.2 MVA, 10 kV) for the study of radial deformation. The
non-parametric statistical methods, namely Spearman correlation coefficient, Wilcoxon signed rank test and Friedman
test are used to compare FRA traces. It was found through this research work that the applied non-parametric methods
can effectively reflect the differences between compared FRA data and diagnose the fault.
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