Detection of shorted turns and winding movements in large power transformers using frequency response analysis

There are various techniques for diagnosing electrical faults in a transformer such as the DDF, tanδ, partial discharges and high voltage tests. But, there are no reliable techniques to identify mechanical faults in a transformer. These faults are winding movement loss of clamping pressure, disc movement etc. Frequency response analysis (FRA) is a tool that can be successfully applied for reliable detection of such faults. In this paper, frequency partitioned mathematical models of a large power transformer is presented and it is shown how the sensitivity of the model parameters can be correlated to inception of transformer faults. Finally, some experimental results are presented