综合消噪算法在金属氧化物避雷器在线监测中的应用  

Application of Comprehensive De-Noising Algorithm to On-Line Monitoring of MOA

作　　者：唐明良[1] 李佑光 曹洪亮[2,3] 

机构地区：[1]重庆大学城市科技学院电气信息学院,重庆402167 [2]南京信息工程大学大气物理学院,南京210044 [3]浙江运达风电股份有限公司,杭州310000

出　　处：《电瓷避雷器》2016年第2期45-49,56,共6页Insulators and Surge Arresters

基　　金：国家自然科学基金项目(编号:41075025);重庆市科学技术研究项目"智能变电站系统建模与测试技术研究"(编号:KJ1502203);重庆市教育科学"十二五"规划课题"应用本科院校学生科技创新实践体系研究"(编号:2013-ZJ-066)

摘　　要：金属氧化物避雷器(MOA)泄漏电流可作为判断其老化的依据。针对实际测量的MOA泄漏电流中存在干扰信号将原始泄漏电流信号覆盖问题,提出卡尔曼滤波和离散平稳小波组合的综合消噪算法。首先使用离散平稳小波将泄漏电流信号分解为细节信号和逼近信号,其次对逼近信号和细节信号滤波进行卡尔曼滤波,最后将滤波后的逼近信号和部分细节信号进行重构,得到消噪后的泄漏电流信号,并首次提出适应于MOA老化的泄漏电流模型对该算法进行仿真验证。研究表明,该综合消噪算法消噪效果明显优于单独使用卡尔曼滤波和离散平稳小波,经过消噪后的泄漏电流波形信噪比明显提升,可从波形上对MOA是否老化进行判断,为MOA在线监测提供依据。The signal of leakage current for metal oxide arrester （MOA） can be used as the basis for judging its aging condition. According to the problem that the actual measurement leakage current for MOA includes an interference signal and which covers the original leakage current, the authors propose a comprehensive de-noising algorithm which composed of Kalman Filter and Discrete Stationary Wavelet. At first, using Discrete Stationary Wavelet to decompose the leakage current as approach and detail signals. Second, using Kalman Filter to processes the approach and detail signals. Finally, the approach and detail signals is reconstructed to get the de-noised leakage current. The model of leakage current which is suitable for MOA after aging is first put forward to prove the algorithm is right. The study shows that the comprehensive de-noising algorithm is better than the Kalman Filter and Discrete Stationary Wavelet, the SNR of the leakage current is obvious improvement. Through the waveform, a judgment whether the MOA aged can be made, it also provides a basis for on-line monitoring MOA.

关 键 词：卡尔曼滤波 平稳小波 消噪 泄漏电流 金属氧化物避雷器 

分 类 号：TM862[电气工程—高电压与绝缘技术]