Affiliation:
1. North China Electric Power University
Abstract
Empirical mode decomposition (EMD), which is the core mechanic of the Hilbert-Huang transform(HHT), is a local, fully data driven and self-adaptive analysis approach. It is a powerful tool for analyzing multi-component signals. Aiming at the reduction of scale mixing and artificial frequency components, an improved scheme was proposed for analysis and reconstruction of nonstationary and multicomponent signals. The improved EMD method uses the wavelet analysis method and normalized correlation coefficient to deal with the problems. Because the inrush current is a peaked wave with nonstationary component, a new algorithm based on improved EMD is presented for fast discrimination between inrush current and fault current of power transformers. Theoretical analysis and dynamic simulation results show that the method is effective and reliable under various fault conditions and simple to be applied.
Publisher
Trans Tech Publications, Ltd.
Reference5 articles.
1. Wang Wei-jian. Eletric Equipment Relay Protection Theory and Application(Second Edition) [M]. Beijing: China Electric Power Press, 2002. pp.98-122.
2. Wang Weijian, Consideration on the Improper Operation of Transformer Protection[J], Automation of Electric Power Systems, 2001, 21(10) , pp.1-3.
3. Huang N E, Shen Z, Long S R et al. The empirical mode decomposition and the hilbert spectrum for nonlinear and nonstationary time series analysis,. Proceedings of the Royal Society of London, (1998).
4. Kizhner S, Blank K, Flatley T, et al. On certain theoretical developments underlying the Hilbert-Huang transform[J]. IEEE Aerospace Conference Proceedings, Big Sky, MT, USA, March (2006).
5. Huang Jiadong, Luo Weiqiang. New algorithm to identify inrush current based on improved mathematical morphology[J]. Proceedings of the CSEE, 2009, 29(7), pp.98-105.