Extraction of Condition Signals of Electrical Plants by ACO Wavelet Threshold Estimation
Long Hongyu1,Zhang Xiaoyong2,Hu Xiaorui2,Feng Shanshan3,Li Long2
1. Southwest University Chongqing 400715 China; 2. Chongqing Electric Power Research Institute Chongqing 401123 China; 3. Zhejiang Hangzhou yuhang Electric Power company Hangzhou 311100 China
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 algorithm and ACO algorithm are utilized for the threshold estimation. The ACO algorithm 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 gradient-based threshold estimation (GTE) 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 GTE. Meanwhile, the ACOTE is a much less time-consuming scheme and exhibits a promising prospect in practical application.
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2015, Vol. 30 
