Transformer winding deformation diagnostics techniques with statistical approach

Abstract

Monitoring the health of power transformer is important for the reliability of electrical power supply. Conventional tests carried out on power transformers can only detect damage of permanent nature. Frequency Response Analysis (FRA) is found to be a useful tool for reliable detection of incipient mechanical fault in a transformer. There are various methods of evaluating the frequency spectrum to confirm the presence of an incipient fault. In this paper two different mechanical fault are simulated i.e. axial displacements and radial deformations of winding. The lumped parameter model is used to simulate these mechanical faults and detected using TF. Since the TF method is a comparative method and the measured results should be compared with the reference results. A comparison shows that resonance frequency of TF curve depends upon type of fault and location of fault. Quantitative analysis of TFs is done using statistical method correlation coefficient as a complementary method. Therefore it is believed that this finding could be helpful in fault diagnosis in actual power transformer windings.