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This paper presents a novel approach to improve the end effects of Hilbert-Huang transform (HHT) for the wind generator fault detection. The proposed approach utilizes a back-propagation neural network (BPNN) to extent the end of the spectrum. HHT consists of empirical mode decomposition (EMD) and Hilbert transform (HT), on which the end effects distort Hilbert spectrum. The extension of the two ends...
This paper presents a novel pattern recognition approach based on a four-layer artificial neural network (ANN) for the partial discharge (PD) diagnosis of power transformer. A precious PD detector is used to measure 3-D (φ-Q-N) signals and PD-fingerprints of four experimental models in a shielded laboratory. This work has established a database containing 160 sets of 3-D patterns and PD-fingerprints...
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