Empirical mode decomposition based denoising of partial discharge signals

-Empirical Mode Decomposition (EMD) has recently been introduced as a local and fully data-driven technique aimed at analyzing nonstationary signals, by decomposing nonstationary signals into Intrinsic Mode Functions (IMFs). In this contribution, we employ it to process the signals of partial discharge, a typical type of nonstationary signal. Based on the IMFs extracted from the corrupted signal, together with the vector threshold, we propose a novel scheme for denoising. By processing of simulation signals and on-site data, it is demonstrated that the proposed method is effective. What is more, the preliminary comparison with waveletbased denoising is performed. Key-Words: Empirical Mode Decomposition, Intrinsic Mode Function, Vector threshold, Partial discharge, White noise, Denoising