基于混沌粒子群的第2代小波的局部放电信号去噪  

Denoising of Partial Discharge Signals by Using SGWT Based on CPSO

作　　者：贾亚飞[1] 李鸿禄[2] 李春耕[2] 朱永利[1] 

机构地区：[1]华北电力大学电气与电子工程学院,保定071003 [2]国网衡水供电公司,衡水053000

出　　处：《电力系统及其自动化学报》2017年第3期62-68,共7页Proceedings of the CSU-EPSA

基　　金：中央高校基本科研业务费专项资金资助项目(2016XS101)

摘　　要：输变电设备局部放电信号在线监测过程会受到多种噪声污染,使得局部放电信号难以提取。该文提出了一种基于混沌粒子群优化算法的第2代小波的去噪方法,在第2代小波及插值细分方法基本原理的基础上,将混沌粒子群优化算法引入预测器和更新器设计中,并改进了重构过程中奇偶序列合并中存在的不匹配问题。通过分别对含有噪声的仿真和实测局部放电信号进行去噪处理,并与传统小波去噪进行对比分析,结果表明基于混沌粒子群优化算法的第2代小波具有快速、高效、实现灵活方便的特点,对局部放电信号具有更好的去噪效果。该方法在局部放电信号处理中有广泛的应用前景。The partial discharge （PD） signals of transmission and transformation equipment during online monitoringare subjected to a variety of noises which leads to the difficulty in extracting PD signals. Therefore a second generationwavelet transform （SGWT） based on chaotic particle swarm optimization （CPSO） is proposed for the denoising of PDsignals in this paper. On the basis of SGWT and subdivision of interpolation CPSO is introduced to the design of predic-tor and updater and the merging procedure of odd and even sequences during reconstruction is improved. The simulatedand measured PD signals are anoised by using the proposed method and the result is compared with that by using tradi-tional wavelet. The result shows that SGWT is rapid efficient and easy to deploy which has better denoising effect on PDsignals. It is indicated that the proposed method has broad application potentials.

关 键 词：局部放电 第2代小波 混沌粒子群 去噪 

分 类 号：TM407[电气工程—电器]