期刊
IEEE TRANSACTIONS ON POWER DELIVERY
卷 20, 期 4, 页码 2414-2421出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRD.2005.852367
关键词
Bayes classifier; high impedance fault; principal component analysis; protection; wavelet transform
A novel method for high impedance fault (HIF) detection i based on pattern recognition systems is presented in this paper. Using this method, HIFs can be discriminated from insulator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching. Wavelet transform is used for the decomposition of signals and feature extraction, feature selection is done by principal component analysis and Bayes classifier is used for classification. HIF and ILC data was acquired from experimental tests and the data for transients was obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying HIFs from other events.
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