New Algorithm to Identify Inrush Current Based on Improved EMD

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.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 6927-6934
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.6927
• Online since: January 2012
• Authors: Da Zhuang Chen, Jia Dong Huang, Yang Sun
• Keywords: Empirical Mode Decomposition (EMD), HHT, Inrush Current, Normalized Correlation Coefficient, Wavelet Analysis

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