This paper proposed a new classification method
based on the discrete wavelet transform (DWT) combined
with an automated classification mechanism based on
adaptive network fuzzy inference system (ANFIS) for power
transformer differential protection to discriminate between
internal faults and no fault condition ( inrush condition) in three
phase power transformers.
For the evaluation of the developed algorithm, transformer
modeling and simulation of fault and no fault condition are
carried using Matlab/Simulink software Package. For each
candidate internal fault or inrush current conditions current
waveform suitable features are extracted by employing
DWT. Then, a successfully trained adaptive network fuzzy
inference system based classifier, developed utilizing inputs
comprising the features extracted from a training set of
waveforms is implemented for a testing set of sample
waveforms. The simulation results obtained show that the
method is faster, more reliable and accurate when compared with
some of published research works in the area.
Keywords: power transformer, inrush current, differential
protection, discrete wavelet transform, adaptive network fuzzy
inference system. |
