Abstract
This paper studied a feature extraction method of GIS optical partial discharge signal. This innovative method is based on multifractal spectrums, which improves from the fractal dimension. Different from the single fractal dimension, the multiple fractal spectrums describe the complexity and inhomogeneity of fractal with more details. In this paper, the fractal dimension and multifractal spectrums of GIS optical partial discharge signal were extracted, and then were recognized by back propagation neural network. By comparing the experimental results, it shows that the multi-fractal spectrum can characterize the optical partial discharge pattern of different insulation defects more effectively, and the classification accuracy is much higher than that of fractal dimension. The results show that the feature of multifractal spectral has great application value in the optical detection of insulation defect in GIS.
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