Denoising electrical signal via empirical mode decomposition

Electric signals are affected by numerous factors, random events, and corrupted with noise, making them nonlinear and non-stationary in nature. In recent years, the application of Empirical Mode Decomposition (EMD) technique to analyze nonlinear and non-stationary signals has gained importance. It is an empirical approach to decompose a signal into a set of oscillatory modes known as intrinsic mode functions (IMFs). Based on an empirical energy model of IMFs, the statistically significant information content is established and combined. In this paper, we demonstrate an approach to detect power quality disturbances in noisy conditions. The approach is based on the statistical properties of fractional Gaussian noise (fGn).