Frequency response interpretation using statistical indices: A case study on 400 MVA transformer

2017

Closed access Metadata (CSL-JSON)
DOI 10.1109/catcon.2017.8280199
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

In the recent past, Frequency Response Analysis (FRA) has been used as a kind of effective method to determine mechanical defects inside the transformer. FRA provides an opportunity to detect mechanical defects without disassembling the transformer active part, whereas visual inspection to identify internal defects is difficult and time consuming. In this study, main statistical indices for FRA result interpretation are introduced and discussed. A failed 400 MVA step-up three-phase transformer is taken as a test object and FRA responses on failed winding are examined through different statistical indices. The outcome and advice of each indicator is also discussed in detail. Finally, the most reliable statistical indices for FRA interpretation are.