Wavelet method optimised by ant colony algorithm used for extracting stable and unstable signals in intelligent substations
作者机构：School of Electrical and Electronic EngineeringChongqing University of TechnologyChongqingChina DepartmentState Key Laboratory of Power Transmission Equipment&System and New TechnologyChongqing UniversityChongqingChina Department of Electrical and Computer EngineeringUniversity of MarylandCollege ParkMarylandUSA
出 版 物：《CAAI Transactions on Intelligence Technology》 (智能技术学报（英文）)
年 卷 期：2022年第7卷第2期
页 面：292-300页
核心收录：
学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学]
基 金：Program of Chongqing Banan District,Grant/Award Number:2020QC407 Chongqing Municipal Education Commission,Grant/Award Number:KJQN202001146 National Key Research and Development Program,Grant/Award Number:2018YFB2100100 Joint Funds of the National Natural Science Foundation of China,Grant/Award Number:U1866603
摘 要：Partial discharge(PD)signals are an important index to evaluate the operation state of intelligent *** correct distinction of PD pulse and interference pulse has become a challenging *** of the noise and the low signal-to-noise ratio,the stable signals become *** selection of a wavelet basis,the selection rule of thresholdλand the design of the threshold function are the key factors affecting the final denoising ***,an enhanced ant colony optimisition wavelet(ACOW)algorithm was applied to find the global optimal threshold through the continuous derivative threshold function and the ant colony optimisation(ACO)*** the same time the efficiency of adaptive search calculation,was also significantly *** method of the ACOW algorithm was compared with the soft wavelet method,gradient-based wavelet method and the genetic optimisation wavelet(GOW)*** these four methods to denoise four typical signals,different mean square errors(MSE),magnitude errors(ME)and time costs were ***,the results show that the ACOW method can achieve the minimum MSE and has less time *** generates significantly smaller waveform distortion than the other three threshold estimation *** addition,the high efficiency and good quality of the output signals are beneficial to the diagnosis of local discharge signals in intelligent substations.
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