13 October 2008 Wavelet-based approach for detection and analysis of transient signal in distributed power system
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Abstract
By combining wavelet transform (WT) with neural network theory, a novel approach is put forward to detect transient fault and analyze voltage stability. The application of signal denoising based on the statistic rule is proposed to determine the threshold of each order of wavelet space. In a view of the inter relationship of wavelet transform and neural network, the whole and local fractal exponents obtained from WT coefficients as features are presented for extracting signal features. The effectiveness of the new algorithm used to extract the characteristic signal is described, which can be realized by the value of those types of transient signal. This model incorporates the advantages of morphological filter and multi-scale WT to extract the feature of fault signal meanwhile restraining various noises. Besides, it can be implemented in real time using the available hardware. The effectiveness of this model was verified with the voltage stability analysis of simulation results.
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Wei Liao, Pu Han, "Wavelet-based approach for detection and analysis of transient signal in distributed power system", Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 71280L (13 October 2008); doi: 10.1117/12.806557; https://doi.org/10.1117/12.806557
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