7. Frequency Response Analysis

Over the last few decades it has been recognized that Frequency Response Analysis (FRA) is a reliable method for detecting dimensional changes in the transformer windings. Out of the two methods of FRA, swept frequency response analysis (SFRA) has gained popularity over the impulse frequency response analysis (IFRA) with the passage of time, although the later was developed first. SFRA is an offline, non-invasive, terminal-based low-voltage measurement, the primary objective of which is to detect even small mechanical deformations accurately. In SFRA the excitation signal of a given frequency is injected to one terminal of the transformer and the response signal is measured at the other end of the winding or at another terminal. Then the transfer function of the winding is computed from the measured excitation and response signals. The frequency of excitation signal is varied over a wide range to detect the deviations in the FRA response, with the help of which the nature of the mechanical fault as well as the quality of insulation could be judged. Frequency dependent parameters of winding such as inductances and capacitances determine the resonant frequencies which appear as peaks and valleys in the FRA transfer functions. Such resonances, which are governed by the poles and zeros of the equivalent network of the transformer winding, appearing in the test case is compared to a no-fault case for identification of fault, if any. There are several comparison techniques that are being used in practice and sometimes more than one technique need to be used simultaneously to arrive at an unambiguous decision. In FRA evaluation processes, it is important to identify the factors that affect the transformer responses in different frequency ranges. There are several terminal configurations of FRA test that may be employed in practice. The sensitivity of the terminal configuration in the detection of mechanical faults is an important issue in FRA. Accurate simulation of FRA response of transformer windings, not only in isolation but also for two-winding transformers, is required for identifying FRA features that could be used for accurate fault identification within an integrated framework. Development of suitable online monitoring system based on SFRA will be helpful in identifying small mechanical faults within transformers in service before such small faults could lead to major faults with severe consequences.