基于最大似然估计的变电站特高频局部放电定向方法

doi:10.19595/j.cnki.1000-6753.tces.180859

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摘要局部放电是电力设备绝缘劣化的早期征兆,其准确检测对电力设备安全稳定运行有重要意义。现有研究侧重于对局部放电脉冲波形进行分析与处理,来解决变电站现场局部放电信号信噪比低、易受干扰的问题,从而提高定向准确度。该文将局部放电定向问题转换为统计分析问题,利用概率统计中的最大似然估计法实现了低信噪比环境下的特高频局部放电准确定向。仿真分析计算及变电站电气试验结果证明,该方法能提高局部放电定向精度,特别是在干扰较多、信噪比较低的变电站环境下（信噪比约5 dB）,定向精度高于传统多信号分类（MUSIC）算法约20%。该文为利用概率统计方法解决局部放电定向问题提供了新思路。

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	周南
	罗林根
	宋辉
	盛戈皞
	江秀臣

关键词 ：局部放电, 特高频, 概率密度, 最大似然估计, 定向

Abstract：Partial discharge (PD) is one of the causes of insulation degradation in electrical equipment. Accurate detection of partial discharge is of great significance to the safety and stability of electrical equipment. The existing research focuses on the analysis and processing of the partial discharge pulse waveform, trying to solve the problem of low signal to noise ratio(SNR) and susceptibility to interference, thereby improving the directional of arrival (DOA) estimation accuracy. In this paper, the problem of PD detection is transferred into a statistical analysis problem. The maximum likelihood estimation method is utilized to solve the problem of ultra-high frequency PD DOA estimation. Simulation analysis and field electrical experiment results showed that the method can improve the accuracy of DOA estimation, especially in substation environment where SNR=5dB. The estimation accuracy of the proposed method increased 20% compared to the traditional MUSIC algorithm. This paper provides a new perspective for solving the PD detection problem by using probability statistics method.

Key words： Partial discharge ultra-high frequency probability density maximum likelihood estimation direction of arrivalestimation

收稿日期: 2018-05-16 出版日期: 2019-08-13

PACS:

TM85

基金资助:国家重点研发计划（2017YFB0902705）和2016年国网公司科技项目（基于特高频无线传感技术的变电站局放在线监测和定位关键技术研究）资助

通讯作者: 罗林根,男,1982年生,博士,研究方向为智能电网、电力系统状态监测等。E-mail：llg523@sjtu.edu.cn

作者简介: 周南男,1993年生,博士研究生,研究方向为电力设备状态监测等。E-mail：zhounan@sjtu.edu.cn

引用本文:

周南, 罗林根, 宋辉, 盛戈皞, 江秀臣. 基于最大似然估计的变电站特高频局部放电定向方法[J]. 电工技术学报, 2019, 34(15): 3285-3292. ZhouNan, LuoLingen, Song Hui, Sheng Gehao, Jiang Xiuchen. A Substation UHF Partial DischargeDirectional of Arrival Estimation MethodBased on Maximum Likelihood Estimation. Transactions of China Electrotechnical Society, 2019, 34(15): 3285-3292.

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[1] 张强, 李成榕.X射线激励下局部放电的研究进展[J]. 电工技术学报, 2017, 32(8):22-32.
Zhang Qiang, Li Chengrong.Review on X-ray induced partial discharge[J]. Transactions of China Electrotechnical Society, 2017, 32(8):22-32.
[2] 刘宇舜, 周文俊, 李鹏飞, 等. 基于广义S变换模时频矩阵的局部放电特高频信号去噪方法[J]. 电工技术学报, 2017, 32(9):211-220.
Liu Yushun, Zhou Wenjun, Li Pengfei, et al.Partial discharge ultrahigh frequency signal denoising method based on generalized S-transform modular time-frequency matrix[J]. Transactions of China Electrotechnical Society, 2017, 32(9): 211-220.
[3] 李臻, 罗林根, 盛戈皞,等. 基于压缩感知的特高频局部放电定位法[J]. 电工技术学报, 2018, 33(1):202-208.
Li Zhen, LuoLingen, Sheng Gehao, et al. Ultrahigh frequency partial discharge localization methodology based on compressed sensing[J]. Transactions of China Electrotechnical Society, 2018, 33(1): 202-208.
[4] 律方成,刘宏宇,李志兵,等. 直流电压下SF₆气体中电极覆膜对金属微粒启举的影响机理[J]. 电工技术学报, 2017, 32(13):239-247.
LüFangcheng, Liu Hongyu, Li Zhibing, et al. Influence mechanism of dielectric coated electrodes on metallic particle lift-off in SF₆ gas under DC voltage[J]. Transactions of China ElectrotechnicalSociety, 2017, 32(13):239-247.
[5] 孙振权, 赵学风, 李继胜,等. 雷电冲击电压下油纸绝缘气隙模型的局部放电测量与分析[J]. 西安交通大学学报, 2009, 43(12):75-80.
Sun Zhenquan, Zhao Xuefeng, Li Jisheng, et al.Partial discharge measurement and analysis of gap in oil-paper insulation model under lightning impulse voltage[J]. Journal of Xi’an Jiaotong University, 2009, 43(12):75-80.
[6] 吕亮,辛晓虎,黄国强,等.用于油中局部放电定位且可重复布置的超声阵列与超高频复合传感器设计[J].高电压技术,2014,40(8):2328-2334.
Lü Liang, XinXiaohu, Huang Guoqiang, et al. Design of re-locatable ultrasonic array and ultra-high frequency combined sensor for partial discharge location in oil[J].High Voltage Engineering, 2014, 40(8): 2328-2334.
[7] 蓝晓宇. 提高空间谱估计分辨率的超分辨测向算法研究[D].哈尔滨:哈尔滨工程大学,2012.
[8] 杨志伟,贺顺,廖桂生.加权伪噪声子空间投影的修正MUSIC算法[J].信号处理,2011,27(1):1-5.
YangZhiwei, He Shun, Liao Guisheng. Modified MUSIC approach with weighted pseudo-noise subspace projection[J]. Signal Processing, 2011, 27(1): 1-5.
[9] 石鹏, 徐凤燕, 王宗欣. 基于传播损耗模型的最大似然估计室内定位算法[J]. 信号处理, 2005, 21(5):502-504.
Shi Peng, XuFengyan, Wang Zongxin. A maximum-likelihood indoor location algorithm based on indoor propagation loss model[J].Signal Processing, 2005, 21(5):502-504.
[10] 石国德, 王明皓, 吕朝晖. 空间谱估计经典算法性能比较[J]. 电子设计工程, 2013, 23(2): 190-193.
Shi Guode, Wang Minghao, LüZhaohui. Performance comparison of spatial spectrum estimation classic algorithm[J]. Electronic Design Engineering, 2013, 23(2): 190-193.
[11] 盛骤, 谢式千, 潘承毅. 概率论与数理统计第四版[M]. 北京: 高等教育出版社, 2010.
[12] 王小英, 陈常龙,尹俊平. 正态分布和瑞利分布混合情形下的参数估计及分类问题[J]. 数学建模及其应用, 2016, 5(3):25-30.
Wang Xiaoying, Chen Changlong, YinJunping. The parameter estimation and classification under mixture model of normal and Rayleighdistribution[J].Mathematical Modeling and Its Application, 2016, 5(3):25-30.
[13] 李军. 极大似然和MUSIC算法用于DOA估计的DSP实现[D].成都:电子科技大学,2005.
[14] 唐炬, 周倩, 许中荣,等.GIS 超高频局部放电信号的数学建模[J]. 中国电机工程学报, 2005, 25(19): 106-110.
TangJu, ZhouQian, XuZhongrong, et al. Establishmentof mathematical model for partial discharge in GIS usingUHF method[J]. Proceedings of the CSEE, 2005, 25(19):106-110.
[15] 薛晓峰, 王永良, 张永顺,等. 二维MUSIC算法分维处理及其阵列结构的研究[J].空军工程大学学报·自然科学版, 2008, 9(5): 33-37.
XueXiaofeng, Wang Yongliang, Zhang Yongshun, et al. A study of decoupling 2D-MUSIC algorithm and array structure[J]. Journal of Air Force Engineering University (Natural Science Edition), 2008, 9(5): 33-37.