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This paper proposes a multi-feature extraction algorithm aiming to recognize disturbances by analyzing synchrophasor data from wide-area monitoring systems. The novel algorithm utilizes wavelet transform (WT) to extract preliminary features from synchrophasors. Two types of features are created by organizing scaling coefficients and wavelet coefficients from WT. The multi-features are compressed by...
Frequency is a vital factor for power system operation and protection. This paper is on extraction of frequency feature for fault/event analysis based on wavelet transform (WT) and fractal geometry (FG). The frequency signal is decomposed by WT-based multiresolution analysis (MRA) and a family of wavelet coefficients is obtained. A maxima line is constructed by connecting the maximum point in the...
By combining wavelet transform (WT) with fractal theory, a novel approach is put forward to detect early short-circuit fault and analyze voltage stability. The application of signal denoising based on the statistic rule is brought forward to determine the threshold of each order of wavelet space, and an effective method is proposed to determine the decomposition level adaptively, increasing the signal-noise-ratio...
By combining wavelet transform (WT) with fractal theory, a novel approach is put forward to detect early short-circuit fault and analyze voltage stability. The application of signal denoising based on the statistic rule is brought forward to determine the threshold of each order of wavelet space, and an effective method is proposed to determine the decomposition level adaptively, increasing the signal-noise-ratio...
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