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- W2892541449 abstract "The automatic pattern recognition of power network fault is important work for power network fault diagnosis in power system. This paper presents automatic pattern recognition methods based on wavelet packet time entropy and support vector machine (SVM) for distribution network operation states. The proposed methods employ wavelet packet time entropy to extract the most important features in the current when the faults happen in the power network. Then the type of power network fault is identified by SVM. The proposed method is found the most suitable pattern recognition tool in the power network fault diagnosis by simulations in typical distribution network. The simulation results show that the method has good performance on pattern recognition with low dimension of eigenvector, less training samples and high classification accuracy." @default.
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- W2892541449 date "2018-05-01" @default.
- W2892541449 modified "2023-09-22" @default.
- W2892541449 title "An Automatic Pattern Recognition Methods for Power Network Fault Diagnosis" @default.
- W2892541449 doi "https://doi.org/10.1109/isgt-asia.2018.8467881" @default.
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