Denoising of Power Quality Disturbance Signal Based on Ant Colony optimization Wavelet Threshold Estimation

Abstract

Based on the problem of the fast and effectively extraction for condition signals of electrical plants in digital substation, this paper presents an approach of ant colony optimization threshold estimation (ACOTE) for de-noising of partial discharge (PD) signals. A class of shrinkage functions with continuous derivatives based on the SURE estimation and ACO estimation are utilized for the threshold estimation. The ACO estimation is competent to obtain the global optimum thresholds and to raise the efficiency of adaptive searching computation. For verifying the de-noising results, two methods of standard soft wavelet threshold estimation (STE) and standard hard wavelet threshold estimation (HTE) are used for de-noising of two typical artificial stable signals, simulative PD signal and the field PD signal. The results show that the white noise can be removed effectively by the ACOTE, the distortion of which is smaller than the signals de-noised by the STE and HTE. Meanwhile, the ACOTE is a much less time-consuming scheme and exhibits a promising prospect in practical application.