New statistical approach to interpret power transformer frequency response analysis: non‐parametric statistical methods. Issue 4 (1st July 2016)

• Record Type: Journal Article
• Authors: Behjat, Vahid; Mahvi, Mojtaba; Rahimpour, Ebrahim
• Is Part Of: IET science, measurement & technology. Volume 10:Issue 4(2016)
• Page Start: 364
• Page End: 369
• Publication Date: 2016-07-01
• Subjects: frequency response -- statistical analysis -- fault diagnosis -- transformer windings -- correlation methods -- power transformer testing; power transformer -- nonparametric statistical method -- frequency response analysis -- mechanical fault detection -- electrical fault detection -- systematic interpretation technique -- parametric statistics -- FRA measurement -- winding distribution transformer -- radial deformation -- Spearman correlation coefficient -- Wilcoxon signed rank test -- Friedman test -- fault diagnosis -- voltage 35 kV -- voltage 0.4 kV -- apparent power 100 kVA -- apparent power 1.2 MVA -- voltage 10 kV; Measurement -- Periodicals; Electrical engineering -- Periodicals; Electronics -- Periodicals; Nanotechnology -- Periodicals; Electromagnetism -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3
• DOI: 10.1049/iet-smt.2015.0204
• Languages: English
• ISSNs: 1751-8822

Abstract

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.