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Partial discharge (PD) measurement and recognition is of great importance to assess the health condition of power transformers. However, the variation of defect size, applied voltage as well as insulation aging gives rise to the dispersion and crossover of PD features, which would influence PD recognition reliability of transformers. An image-oriented two-directional modified fuzzy-weighted two-dimensional...
This paper presents a feature extraction algorithm combining S transform (ST) and two-directional two-dimensional principal component analysis ((2D)2 PCA) for partial discharge (PD) pattern recognition. S transform (ST) is firstly employed to obtain a time-frequency representation of the recorded UHF signals. Then, (2D)2 PCA is applied to compress the ST amplitude(STA) matrices to extract various...
In this paper, an electronic nose data classification approach based on least square support vector machines (LS-SVM) in combination with principal component analysis (PCA) is investigated. The electronic nose data are first converted into PCA, where the data are projected from a high dimensional space into a low dimensional space, preferably two or three dimensions. Then the resulting features from...
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