Abstract: An interpolating windowed discrete Fourier transform (DFT) has been used to eliminate
the errors caused by the leakage and picket fence effects associated with use of a conventional
DFT. An interpolating algorithm eliminates the errors caused by the picket fence effect, and the
errors produced by the leakage effect are reduced by windowing the signals. The precision of the
harmonic analysis and the implementation of the interpolating algorithm are both affected by
the choice of window function. The leakage effect of a conventional DFT and the windowed DFT
are analysed. A method to construct optimal window functions and the corresponding
interpolation algorithms is presented. Simulation results show that the interpolating windowed
DFT algorithms have a high accuracy and are easy to implement and they are therefore useful
tools for precise and practical harmonics evaluation in power systems.
Taking advantage of S-transform(ST), the paper
proposes a new method of detecting and classifying power quality
disturbances. The S-transform is unique in that it provides
frequency-dependent resolution while maintaining a direct
relationship with the Fourier spectrum. The features obtained
from S-transform are distinct, understandable and immune to
noise. According to a rule-based decision tree, eight types of
single power disturbance and two types of complex power
disturbance are well recognized, and there is no need to use other
complicated classifiers. The comparison between the Wavelettransform-
based method and the S-transform-based method for
power quality disturbance recognition is also provided. The
simulation results show that the proposed method is effective and
immune against noise. The proposed method is feasible and
promising for real applications.
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发表于 2009-10-27 17:36:09
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