西安交通大学电气工程学院,西安,710049
网络首发:2008-10-10,
纸质出版:2008
移动端阅览
司文荣, 李军浩, 梁永春, 等. 采用独立成分分析的局部放电脉冲双通道提取技术研究[J]. 西安交通大学学报, 2008,42(10):1264-1268+1294.
司文荣, 李军浩, 梁永春, et al. Pulse Extraction for Partial Discharge with Double Channels with Independent Component Analysis[J]. 2008, 42(10): 1264-1268+1294.
简单介绍了独立成分分析(ICA)基本模型的假设、含混性问题及模型估计的等变化性.根据局部放电脉冲序列幅值的超高斯分布特性以及实际工况下的其他条件
得出了将ICA基本模型用于强背景白噪声下微弱局部放电脉冲信号提取的可行性.针对IEC60270规定的标准脉冲电流法
基于双通道超宽带检测
对试品放电状态下的脉冲提取进行了仿真
对直流下油纸绝缘针板模型进行局部放电实验
并给出直流下局部放电脉冲提取的ICA含混性消除方法.实验结果表明
该方法能够提取出被白噪声完全淹没的局部放电脉冲信号
可以恢复出局部放电波形之间相对幅值关系和单个脉冲波形以及脉冲极值所对应的时间点等重要局部放电信息.
The assumption
ambiguities
and solution of basic independent component analysis(ICA)model are briefly introduced. According to the features of white noise(gaussian)and partial discharge(PD)signals(supergaussian)on the probability distribution of magnitude
and the IEC 60270 standard PD measurement method
it indicates that the basic ICA model is feasible to suppress white noise of PD pulse signals. The simulation and on field tests for PD pulses extraction using ultra-wideband(UWB)detection technique with double channels are carried out
respectively. And the ambiguities elimination method for ICA model to extract PD pulses under HVDC is also presented. The results show that PD pulses are able to be exactly extracted from the strong white noise with keeping PD pulses amplitude of the relative relationship
the maximum amplitude corresponding to the time point
and the other important information of PD pulses.
CONTIN A, CAVALLINI A, MONTANARI G C. Digital detection and fuzzy classification of partial discharge signals[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2002, 9(3): 335-348.
MA X, ZHOU C, KEMP I J. Interpretation of wavelet analysis and it's application in partial discharge detection[J]. IEEE Trans Dielect Elect Insul, 2002,9(2): 446-457.
李洪, 孙云莲. 基于独立分量分析的局部放电脉冲信号提取[J]. 电力系统及其自动化学报, 2007, 19(2): 78-81.
LI Hong, SUN Yunlian. Extraction of partial discharge signals using independent component analysis[J]. Proceeding of the CSU-EPSA, 2007, 19(2): 78-81.
张海军, 温广瑞, 屈梁生. 一种提高诊断信息质量的方法[J]. 西安交通大学学报, 2002, 36(3): 295-299.
ZHANG Haijun, WEN Guangrui, QU Liangsheng. Method to improve the quality of diagnostic information[J]. Journal of Xi'an Jiaotong University, 2002, 36(3): 295-299.
李力, 屈梁生. 应用独立分量分析提取机器的状态特征[J]. 西安交通大学学报, 2003, 37(1): 45-48.
LI Li, QU Liangsheng. Independent component analysis for features extraction of machine condition[J]. Journal of Xi'an Jiaotong University, 2003, 37(1): 45-48.
杨福生, 洪波. 独立分量分析的原理和应用[M].北京:清华大学出版社, 2006.
周宗潭, 董国华, 徐昕,等. 独立分量分析[M].北京:电子工业出版社, 2007.
焦卫东. 基于独立分量分析的旋转机械故障诊断[D]. 杭州:浙江大学电气工程学院, 2003.
司文荣,李军浩,李彦明,等.局部放电脉冲信号ICA提取技术的初步研究[J].高电压技术,2008,34(6):1277-1282.
SI Wenrong, LI Junhao, LI Yanming, et al. Preliminary study on signal extraction technology for PD pulse based on independent component analysis [J].High Voltage Engineering, 2008, 34(6): 1277-1282.
PETER H F, JOHAN J. Partial discharges at dc voltage: their mechanism, detection and analysis[J]. IEEE Trans on Dielectrics and Electrical Insulation, 2005, 12(2): 328-340.
司文荣, 李军浩, 李彦明,等. 直流下油中局部放电脉冲波形测量与特性分析[J]. 西安交通大学学报, 2008, 42(4): 481-486.
SI Wenrong, LI Junhao, LI Yanming, et al. Measurement and analysis for pulse current shapes of partial discharge in oil under DC voltage[J]. Journal of Xi'an Jiaotong University, 2008, 42(4): 481-486.
0
浏览量
5
下载量
2
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621