Noise and zero excursion elimination of electrostatic detection signals based on EMD and wavelet transform

Electrostatic detection signals are often corrupted by high frequency noise, power line interference and zero excursion. In order to extract and identify the characteristic points of electrostatic signal correctly, an algorithm combining empirical mode decomposition (EMD) and wavelet threshold de-noising was proposed. Based on the analysis of EMD results, this method applied wavelet threshold de-noising to several high order intrinsic mode functions (IMFs) and recovered the electrostatic signal by the de-noised IMFs. Experiments on several electrostatic detection signals with different noise parameters were carried out to evaluate the performance of the proposed method. The simulation results show that this method is superior to EMD de-noising and wavelet threshold de-noising both in SNR and variance. In addition, it eliminates zero excursion by subtracting the residual signal, which brings great benefit to the recognition of zero-crossing. The proposed method eliminating noise and zero excursion adaptively, provides an effective way to process the electrostatic detection signals.