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Principal Component Sparse and Its Application in GIS Partial Discharge Feature Extraction
Pages: 282-288
Year: Issue:  8
Journal: Transactions of China Electrotechnical Society

Keyword:  Gas insulated switchgearpartial dischargeprincipal componentsparsefeature extraction;
Abstract: Feature extraction is the key to GIS partial discharge pattern recognition, usually, the dimension of feature space is high, which is not conductive to classification. Based on this, the article introduce the principal component sparse thoughts, first of all, through the 252 k V GIS partial discharge simulation experiment platform, set up the typical GIS partial discharge models, and uses ultrasound to obtain the corresponding signals, and then, through the principal component contribution rate to decide the degree of sparse, the results show that using this method can realize effective extraction of characteristic, and enhance the clustering results.
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