互补集成经验模态分解在MOA监测中的应用  

Application of Complete Ensemble Empirical Mode Decomposition in MOA Monitoring

作　　者：何贵先[1,2] 行鸿彦[1,2] 徐伟[1] 季鑫源[1] HE Guixian;XING Hongyan;XU Wei;JI Xinyuan(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &Technology,Nanjing210044,China;Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,Nanjing University of Information Science &Technology,Nanjing210044,China)

机构地区：[1]南京信息工程大学气象灾害预报预警与评估协同创新中心,南京210044 [2]南京信息工程大学中国气象局气溶胶与云降水重点开发实验室,南京210044

出　　处：《高压电器》2018年第12期225-231,共7页High Voltage Apparatus

基　　金：国家自然科学基金(61671248;41605121);江苏省高校自然科学研究重大项目(15KJA460008);江苏省"信息与通信工程"优势学科~~

摘　　要：针对金属氧化物避雷器在线监测中提取持续电流信号含噪声的问题,提出了基于互补集成经验模态分解(CEEMDAN)的避雷器持续电流去噪方法。将含噪电流信号分解成一系列固有模态函数(IMF),对分解后的IMF进行自相关分析,选出有用信号和含噪分量,对含噪的IMF进行SG (savitzky-golay)滤波去噪,将滤波后的模态分量与剩余的分量进行重构得到消噪后的持续电流信号。MATLAB仿真结果表明:正常情况和老化情况下的MOA去噪后的持续电流均方根误差(正常:3.209 8×10-5,老化:0.002 5)比去噪前的(正常:2.450 9×10-4,老化:0.017 3)均降低了一个数量级,说明该方法有效消除了噪声对避雷器持续电流信号提取的影响,保证了MOA进一步监测分析的准确性。According to the detection of continuous current of metal oxide arrester(MOA)comprises lots of noises,a de-noise method is proposed based on Complete Ensemble Empirical Mode Decomposition(CEEMDAN).The detection signals with noise of MOA can be decomposed into a series of intrinsic mode functions(IMFs),and then the IMFs are analyzed by auto correlation.In order to get useful components and noise components,the Savitzky-Golay filter is used to de-noise.After filtering,the remaining components are restricted into a new signal.A typical surge arrester has been simulated in MATLAB,and the result shows that by de-noising of the continuous current of MOA,the root mean square error can be reduced by one order of magnitude(normal 3.209 8×10-5,aging 0.002 5),while the model before de-noising(normal 2.450 9×10-4,aging 0.017 3),and the effectiveness of the proposed method is verified,the accuracy of MOA monitoring results are improved.

关 键 词：互补集成经验模态分解 金属氧化物避雷器 持续电流 自相关函数 SG滤波 

分 类 号：TM862[电气工程—高电压与绝缘技术]