Denoising of Electrical Shock Fault Signal based on Empirical Mode Decomposition Thresholding

The electrical shock fault signal is very important to the protection and control of power system. However, in practical cases, the signal is usually corrupted by artifacts through the recording process. Thus, denoising of this type of electric shock fault signals seems necessary. In this paper, a novel method for denoising electriccal shock fault signals is proposed based on Empirical mode Decomposition-Thresholding (EMD-T). With the new method, the nonlinear and non-stationary fault signal is decomposed into intrinsic mode functions (IMFs) via EMD, then, mixed modes will be processed by threshold denoising approach. The efficiency of the method is applied on real electric shock fault signals and white Gaussian noise added electrical shock fault signals obtained from Residual Current Operated Protective Device experiment platform. Signal to Noise Ratio (SNR) and Root Mean Square Error (MSE) are used to measure and compare the performance of proposed method with traditional FIR based method. Results show that EMD-T algorithm performs better than conventional FIR filter method.