Søren Damsgaard Mikkelsen

Detection of faults and ageing phenomena in transformers by transfer functions

In this paper the performance of a new transformer diagnosis method is tested experimentally. The method is called model-based diagnosis because the diagnosis is based on an identified model of the component-the transfer function. Two test series are carried out to evaluate the method on transformers, a sensitivity test series and an ageing test series. The purpose of the sensitivity test series is to determine how close the identified transformer model is connected to the physical condition of the modelled transformer. The purpose of the ageing test series is to determine if it is possible to identify a development in the transfer function of the transformer towards breakdown. Based on the two test series it is concluded that the detection of failures and ageing phenomena in transformers by transfer functions is dependent on detectable changes in relatively few characteristic transformer parameters-basically lumped winding capacitances, total losses and core reluctance. >

Parametric identification in potential transformer modelling

It is shown that a wideband lumped parameter equivalent circuit of a potential transformer can be determined through parametric system identification by the least squares method. Because of limitations in the measuring equipment, up to four different sets of input/output signals are necessary. Compared with other tests for finding the equivalent circuit, this method is less time consuming. Results obtained on a 50 Hz (20/ square root 3) kV/(110/ square root 3) V potential transformer are presented. >

Sensitivity of identified transfer functions in transformer diagnosis

The performance of a new transformer diagnosis method is tested experimentally. The method is called model-based diagnosis because the diagnosis is based on an identified model of the component, i.e., the transfer function. A single test series is carried out in order to evaluate the sensitivity of the method in transformer diagnosis. The basic purpose of this sensitivity test series is to determine how close the identified transformer model is connected to the physical condition of the modeled transformer. Based on the results of the sensitivity test series it is concluded that the detection of failures and aging phenomena in transformers by transfer functions is dependent on detectable changes in relatively few characteristic transformer parameters, i.e., basically lumped winding capacitances, total losses and core reluctance.

Curve-fitting method for transfer function determination

A curve-fitting method for determination of transfer functions by frequency sweep analysis is established. The method uses linearization of the modeled signals by use of a Taylors series and minimization of the error between the estimated and the measured values by the least-squares method. It is found that the transfer function determined by this method is more certain and stable than it would be if the transfer function were determined by detecting maximum amplitudes and zero-crossings of the input/output signals even if these signals had been averaged and filtered. Some errors are detected in the phase angles at very low currents, but the errors are within +or-30 degrees.<<ETX>>